{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Task2 数据分析\n",
    "\n",
    "## 任务目标：\n",
    "\n",
    "1. 熟悉了解整个数据集的基本情况\n",
    "2. 了解变量间的相互关系\n",
    "3. 为特征工程做准备"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 导入需要的库"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt \n",
    "import seaborn as sns\n",
    "import datetime\n",
    "import warnings \n",
    "warnings.filterwarnings('ignore')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 读取文件"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "data_train = pd.read_csv('../train.csv')\n",
    "data_test_a = pd.read_csv('../testA.csv')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 查看数据集样本个数和原始特征维度"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(800000, 47)"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_train.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(200000, 46)"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_test_a.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['id', 'loanAmnt', 'term', 'interestRate', 'installment', 'grade',\n",
       "       'subGrade', 'employmentTitle', 'employmentLength', 'homeOwnership',\n",
       "       'annualIncome', 'verificationStatus', 'issueDate', 'isDefault',\n",
       "       'purpose', 'postCode', 'regionCode', 'dti', 'delinquency_2years',\n",
       "       'ficoRangeLow', 'ficoRangeHigh', 'openAcc', 'pubRec',\n",
       "       'pubRecBankruptcies', 'revolBal', 'revolUtil', 'totalAcc',\n",
       "       'initialListStatus', 'applicationType', 'earliesCreditLine', 'title',\n",
       "       'policyCode', 'n0', 'n1', 'n2', 'n3', 'n4', 'n5', 'n6', 'n7', 'n8',\n",
       "       'n9', 'n10', 'n11', 'n12', 'n13', 'n14'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_train.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 800000 entries, 0 to 799999\n",
      "Data columns (total 47 columns):\n",
      "id                    800000 non-null int64\n",
      "loanAmnt              800000 non-null float64\n",
      "term                  800000 non-null int64\n",
      "interestRate          800000 non-null float64\n",
      "installment           800000 non-null float64\n",
      "grade                 800000 non-null object\n",
      "subGrade              800000 non-null object\n",
      "employmentTitle       799999 non-null float64\n",
      "employmentLength      753201 non-null object\n",
      "homeOwnership         800000 non-null int64\n",
      "annualIncome          800000 non-null float64\n",
      "verificationStatus    800000 non-null int64\n",
      "issueDate             800000 non-null object\n",
      "isDefault             800000 non-null int64\n",
      "purpose               800000 non-null int64\n",
      "postCode              799999 non-null float64\n",
      "regionCode            800000 non-null int64\n",
      "dti                   799761 non-null float64\n",
      "delinquency_2years    800000 non-null float64\n",
      "ficoRangeLow          800000 non-null float64\n",
      "ficoRangeHigh         800000 non-null float64\n",
      "openAcc               800000 non-null float64\n",
      "pubRec                800000 non-null float64\n",
      "pubRecBankruptcies    799595 non-null float64\n",
      "revolBal              800000 non-null float64\n",
      "revolUtil             799469 non-null float64\n",
      "totalAcc              800000 non-null float64\n",
      "initialListStatus     800000 non-null int64\n",
      "applicationType       800000 non-null int64\n",
      "earliesCreditLine     800000 non-null object\n",
      "title                 799999 non-null float64\n",
      "policyCode            800000 non-null float64\n",
      "n0                    759730 non-null float64\n",
      "n1                    759730 non-null float64\n",
      "n2                    759730 non-null float64\n",
      "n3                    759730 non-null float64\n",
      "n4                    766761 non-null float64\n",
      "n5                    759730 non-null float64\n",
      "n6                    759730 non-null float64\n",
      "n7                    759730 non-null float64\n",
      "n8                    759729 non-null float64\n",
      "n9                    759730 non-null float64\n",
      "n10                   766761 non-null float64\n",
      "n11                   730248 non-null float64\n",
      "n12                   759730 non-null float64\n",
      "n13                   759730 non-null float64\n",
      "n14                   759730 non-null float64\n",
      "dtypes: float64(33), int64(9), object(5)\n",
      "memory usage: 286.9+ MB\n"
     ]
    }
   ],
   "source": [
    "data_train.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>loanAmnt</th>\n",
       "      <th>term</th>\n",
       "      <th>interestRate</th>\n",
       "      <th>installment</th>\n",
       "      <th>employmentTitle</th>\n",
       "      <th>homeOwnership</th>\n",
       "      <th>annualIncome</th>\n",
       "      <th>verificationStatus</th>\n",
       "      <th>isDefault</th>\n",
       "      <th>...</th>\n",
       "      <th>n5</th>\n",
       "      <th>n6</th>\n",
       "      <th>n7</th>\n",
       "      <th>n8</th>\n",
       "      <th>n9</th>\n",
       "      <th>n10</th>\n",
       "      <th>n11</th>\n",
       "      <th>n12</th>\n",
       "      <th>n13</th>\n",
       "      <th>n14</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>800000.000000</td>\n",
       "      <td>800000.000000</td>\n",
       "      <td>800000.000000</td>\n",
       "      <td>800000.000000</td>\n",
       "      <td>800000.000000</td>\n",
       "      <td>799999.000000</td>\n",
       "      <td>800000.000000</td>\n",
       "      <td>8.000000e+05</td>\n",
       "      <td>800000.000000</td>\n",
       "      <td>800000.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>759730.000000</td>\n",
       "      <td>759730.000000</td>\n",
       "      <td>759730.000000</td>\n",
       "      <td>759729.000000</td>\n",
       "      <td>759730.000000</td>\n",
       "      <td>766761.000000</td>\n",
       "      <td>730248.000000</td>\n",
       "      <td>759730.000000</td>\n",
       "      <td>759730.000000</td>\n",
       "      <td>759730.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>399999.500000</td>\n",
       "      <td>14416.818875</td>\n",
       "      <td>3.482745</td>\n",
       "      <td>13.238391</td>\n",
       "      <td>437.947723</td>\n",
       "      <td>72005.351714</td>\n",
       "      <td>0.614213</td>\n",
       "      <td>7.613391e+04</td>\n",
       "      <td>1.009683</td>\n",
       "      <td>0.199513</td>\n",
       "      <td>...</td>\n",
       "      <td>8.107937</td>\n",
       "      <td>8.575994</td>\n",
       "      <td>8.282953</td>\n",
       "      <td>14.622488</td>\n",
       "      <td>5.592345</td>\n",
       "      <td>11.643896</td>\n",
       "      <td>0.000815</td>\n",
       "      <td>0.003384</td>\n",
       "      <td>0.089366</td>\n",
       "      <td>2.178606</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>230940.252013</td>\n",
       "      <td>8716.086178</td>\n",
       "      <td>0.855832</td>\n",
       "      <td>4.765757</td>\n",
       "      <td>261.460393</td>\n",
       "      <td>106585.640204</td>\n",
       "      <td>0.675749</td>\n",
       "      <td>6.894751e+04</td>\n",
       "      <td>0.782716</td>\n",
       "      <td>0.399634</td>\n",
       "      <td>...</td>\n",
       "      <td>4.799210</td>\n",
       "      <td>7.400536</td>\n",
       "      <td>4.561689</td>\n",
       "      <td>8.124610</td>\n",
       "      <td>3.216184</td>\n",
       "      <td>5.484104</td>\n",
       "      <td>0.030075</td>\n",
       "      <td>0.062041</td>\n",
       "      <td>0.509069</td>\n",
       "      <td>1.844377</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>500.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>5.310000</td>\n",
       "      <td>15.690000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>199999.750000</td>\n",
       "      <td>8000.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>9.750000</td>\n",
       "      <td>248.450000</td>\n",
       "      <td>427.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>4.560000e+04</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>9.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>8.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>399999.500000</td>\n",
       "      <td>12000.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>12.740000</td>\n",
       "      <td>375.135000</td>\n",
       "      <td>7755.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>6.500000e+04</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>7.000000</td>\n",
       "      <td>7.000000</td>\n",
       "      <td>7.000000</td>\n",
       "      <td>13.000000</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>11.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>599999.250000</td>\n",
       "      <td>20000.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>15.990000</td>\n",
       "      <td>580.710000</td>\n",
       "      <td>117663.500000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>9.000000e+04</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>11.000000</td>\n",
       "      <td>11.000000</td>\n",
       "      <td>10.000000</td>\n",
       "      <td>19.000000</td>\n",
       "      <td>7.000000</td>\n",
       "      <td>14.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>3.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>799999.000000</td>\n",
       "      <td>40000.000000</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>30.990000</td>\n",
       "      <td>1715.420000</td>\n",
       "      <td>378351.000000</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>1.099920e+07</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>70.000000</td>\n",
       "      <td>132.000000</td>\n",
       "      <td>79.000000</td>\n",
       "      <td>128.000000</td>\n",
       "      <td>45.000000</td>\n",
       "      <td>82.000000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>39.000000</td>\n",
       "      <td>30.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>8 rows × 42 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                  id       loanAmnt           term   interestRate  \\\n",
       "count  800000.000000  800000.000000  800000.000000  800000.000000   \n",
       "mean   399999.500000   14416.818875       3.482745      13.238391   \n",
       "std    230940.252013    8716.086178       0.855832       4.765757   \n",
       "min         0.000000     500.000000       3.000000       5.310000   \n",
       "25%    199999.750000    8000.000000       3.000000       9.750000   \n",
       "50%    399999.500000   12000.000000       3.000000      12.740000   \n",
       "75%    599999.250000   20000.000000       3.000000      15.990000   \n",
       "max    799999.000000   40000.000000       5.000000      30.990000   \n",
       "\n",
       "         installment  employmentTitle  homeOwnership  annualIncome  \\\n",
       "count  800000.000000    799999.000000  800000.000000  8.000000e+05   \n",
       "mean      437.947723     72005.351714       0.614213  7.613391e+04   \n",
       "std       261.460393    106585.640204       0.675749  6.894751e+04   \n",
       "min        15.690000         0.000000       0.000000  0.000000e+00   \n",
       "25%       248.450000       427.000000       0.000000  4.560000e+04   \n",
       "50%       375.135000      7755.000000       1.000000  6.500000e+04   \n",
       "75%       580.710000    117663.500000       1.000000  9.000000e+04   \n",
       "max      1715.420000    378351.000000       5.000000  1.099920e+07   \n",
       "\n",
       "       verificationStatus      isDefault      ...                   n5  \\\n",
       "count       800000.000000  800000.000000      ...        759730.000000   \n",
       "mean             1.009683       0.199513      ...             8.107937   \n",
       "std              0.782716       0.399634      ...             4.799210   \n",
       "min              0.000000       0.000000      ...             0.000000   \n",
       "25%              0.000000       0.000000      ...             5.000000   \n",
       "50%              1.000000       0.000000      ...             7.000000   \n",
       "75%              2.000000       0.000000      ...            11.000000   \n",
       "max              2.000000       1.000000      ...            70.000000   \n",
       "\n",
       "                  n6             n7             n8             n9  \\\n",
       "count  759730.000000  759730.000000  759729.000000  759730.000000   \n",
       "mean        8.575994       8.282953      14.622488       5.592345   \n",
       "std         7.400536       4.561689       8.124610       3.216184   \n",
       "min         0.000000       0.000000       1.000000       0.000000   \n",
       "25%         4.000000       5.000000       9.000000       3.000000   \n",
       "50%         7.000000       7.000000      13.000000       5.000000   \n",
       "75%        11.000000      10.000000      19.000000       7.000000   \n",
       "max       132.000000      79.000000     128.000000      45.000000   \n",
       "\n",
       "                 n10            n11            n12            n13  \\\n",
       "count  766761.000000  730248.000000  759730.000000  759730.000000   \n",
       "mean       11.643896       0.000815       0.003384       0.089366   \n",
       "std         5.484104       0.030075       0.062041       0.509069   \n",
       "min         0.000000       0.000000       0.000000       0.000000   \n",
       "25%         8.000000       0.000000       0.000000       0.000000   \n",
       "50%        11.000000       0.000000       0.000000       0.000000   \n",
       "75%        14.000000       0.000000       0.000000       0.000000   \n",
       "max        82.000000       4.000000       4.000000      39.000000   \n",
       "\n",
       "                 n14  \n",
       "count  759730.000000  \n",
       "mean        2.178606  \n",
       "std         1.844377  \n",
       "min         0.000000  \n",
       "25%         1.000000  \n",
       "50%         2.000000  \n",
       "75%         3.000000  \n",
       "max        30.000000  \n",
       "\n",
       "[8 rows x 42 columns]"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_train.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>loanAmnt</th>\n",
       "      <th>term</th>\n",
       "      <th>interestRate</th>\n",
       "      <th>installment</th>\n",
       "      <th>grade</th>\n",
       "      <th>subGrade</th>\n",
       "      <th>employmentTitle</th>\n",
       "      <th>employmentLength</th>\n",
       "      <th>homeOwnership</th>\n",
       "      <th>...</th>\n",
       "      <th>n5</th>\n",
       "      <th>n6</th>\n",
       "      <th>n7</th>\n",
       "      <th>n8</th>\n",
       "      <th>n9</th>\n",
       "      <th>n10</th>\n",
       "      <th>n11</th>\n",
       "      <th>n12</th>\n",
       "      <th>n13</th>\n",
       "      <th>n14</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>35000.0</td>\n",
       "      <td>5</td>\n",
       "      <td>19.52</td>\n",
       "      <td>917.97</td>\n",
       "      <td>E</td>\n",
       "      <td>E2</td>\n",
       "      <td>320.0</td>\n",
       "      <td>2 years</td>\n",
       "      <td>2</td>\n",
       "      <td>...</td>\n",
       "      <td>9.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>18000.0</td>\n",
       "      <td>5</td>\n",
       "      <td>18.49</td>\n",
       "      <td>461.90</td>\n",
       "      <td>D</td>\n",
       "      <td>D2</td>\n",
       "      <td>219843.0</td>\n",
       "      <td>5 years</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>13.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>12000.0</td>\n",
       "      <td>5</td>\n",
       "      <td>16.99</td>\n",
       "      <td>298.17</td>\n",
       "      <td>D</td>\n",
       "      <td>D3</td>\n",
       "      <td>31698.0</td>\n",
       "      <td>8 years</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>21.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>11000.0</td>\n",
       "      <td>3</td>\n",
       "      <td>7.26</td>\n",
       "      <td>340.96</td>\n",
       "      <td>A</td>\n",
       "      <td>A4</td>\n",
       "      <td>46854.0</td>\n",
       "      <td>10+ years</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>16.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>21.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>3000.0</td>\n",
       "      <td>3</td>\n",
       "      <td>12.99</td>\n",
       "      <td>101.07</td>\n",
       "      <td>C</td>\n",
       "      <td>C2</td>\n",
       "      <td>54.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>4.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 47 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   id  loanAmnt  term  interestRate  installment grade subGrade  \\\n",
       "0   0   35000.0     5         19.52       917.97     E       E2   \n",
       "1   1   18000.0     5         18.49       461.90     D       D2   \n",
       "2   2   12000.0     5         16.99       298.17     D       D3   \n",
       "3   3   11000.0     3          7.26       340.96     A       A4   \n",
       "4   4    3000.0     3         12.99       101.07     C       C2   \n",
       "\n",
       "   employmentTitle employmentLength  homeOwnership ...     n5    n6    n7  \\\n",
       "0            320.0          2 years              2 ...    9.0   8.0   4.0   \n",
       "1         219843.0          5 years              0 ...    NaN   NaN   NaN   \n",
       "2          31698.0          8 years              0 ...    0.0  21.0   4.0   \n",
       "3          46854.0        10+ years              1 ...   16.0   4.0   7.0   \n",
       "4             54.0              NaN              1 ...    4.0   9.0  10.0   \n",
       "\n",
       "     n8   n9   n10  n11  n12  n13  n14  \n",
       "0  12.0  2.0   7.0  0.0  0.0  0.0  2.0  \n",
       "1   NaN  NaN  13.0  NaN  NaN  NaN  NaN  \n",
       "2   5.0  3.0  11.0  0.0  0.0  0.0  4.0  \n",
       "3  21.0  6.0   9.0  0.0  0.0  0.0  1.0  \n",
       "4  15.0  7.0  12.0  0.0  0.0  0.0  4.0  \n",
       "\n",
       "[5 rows x 47 columns]"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_train.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 查看数据集中特征的缺失值，唯一值"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "数据集中有22列具有缺失值\n"
     ]
    }
   ],
   "source": [
    "print('数据集中有%s列具有缺失值' % (data_train.isnull().any().sum()))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1175b0a50>"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# nan可视化\n",
    "missing = data_train.isnull().sum()/len(data_train) \n",
    "missing = missing[missing > 0] \n",
    "missing.sort_values(inplace=True) \n",
    "missing.plot.bar()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "了解哪些列存在 “nan”, 并可以把nan的个数打印，主要的目的在于 nan存在的个数是否真的很大，如果很小一般选 择填充，如果使用lgb等树模型可以直接空缺，让树自己去优化，但如果nan存在的过多、可以考虑删掉"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 查看训练集测试集中特征属性只有一值的特征"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "one_value_feature = [col for col in data_train.columns if data_train[col].nunique() <= 1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['policyCode']"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "one_value_feature"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 总结:\n",
    "47列数据中有22列都缺少数据，这在现实世界中很正常。‘policyCode’具有一个唯一值(或全部缺失)。有很多连续变量和一些分类变量。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 查看特征有哪些类型\n",
    "1. 特征一般都是由类别型特征和数值型特征组成 \n",
    "2. 类别型特征有时具有非数值关系，有时也具有数值关系。比如‘grade’中的等级A，B，C等，是否只是单纯的分类，还是A优于其他要结合业务判断。 \n",
    "3. 数值型特征本是可以直接在模型中使用的，但是对一些线性模型来说，一般是会进行分箱。从模型效果上来看，特征分箱主要是为了降低变量的复杂性，减少变量噪音对模型的影响，提高自变量 和因变量的相关度。从而使模型更加稳定。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "numerical_fea = list(data_train.select_dtypes(exclude=['object']).columns) \n",
    "category_fea = list(filter(lambda x: x not in numerical_fea,list(data_train.columns)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['id',\n",
       " 'loanAmnt',\n",
       " 'term',\n",
       " 'interestRate',\n",
       " 'installment',\n",
       " 'employmentTitle',\n",
       " 'homeOwnership',\n",
       " 'annualIncome',\n",
       " 'verificationStatus',\n",
       " 'isDefault',\n",
       " 'purpose',\n",
       " 'postCode',\n",
       " 'regionCode',\n",
       " 'dti',\n",
       " 'delinquency_2years',\n",
       " 'ficoRangeLow',\n",
       " 'ficoRangeHigh',\n",
       " 'openAcc',\n",
       " 'pubRec',\n",
       " 'pubRecBankruptcies',\n",
       " 'revolBal',\n",
       " 'revolUtil',\n",
       " 'totalAcc',\n",
       " 'initialListStatus',\n",
       " 'applicationType',\n",
       " 'title',\n",
       " 'policyCode',\n",
       " 'n0',\n",
       " 'n1',\n",
       " 'n2',\n",
       " 'n3',\n",
       " 'n4',\n",
       " 'n5',\n",
       " 'n6',\n",
       " 'n7',\n",
       " 'n8',\n",
       " 'n9',\n",
       " 'n10',\n",
       " 'n11',\n",
       " 'n12',\n",
       " 'n13',\n",
       " 'n14']"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "numerical_fea"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['grade', 'subGrade', 'employmentLength', 'issueDate', 'earliesCreditLine']"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "category_fea"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 数值变量分析\n",
    "数值型变量包括连续型变量与离散型变量"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "划分数值型变量中的连续变量和分类变量"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "#过滤数值型类别特征\n",
    "def get_numerical_serial_fea(data,feas):\n",
    "    numerical_serial_fea = [] \n",
    "    numerical_noserial_fea = [] \n",
    "    for fea in feas:\n",
    "        temp = data[fea].nunique() \n",
    "        if temp <= 10:\n",
    "            numerical_noserial_fea.append(fea)\n",
    "            continue\n",
    "        numerical_serial_fea.append(fea)\n",
    "    return numerical_serial_fea,numerical_noserial_fea\n",
    "numerical_serial_fea,numerical_noserial_fea = get_numerical_serial_fea(data_train,numerical_fea)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['id',\n",
       " 'loanAmnt',\n",
       " 'interestRate',\n",
       " 'installment',\n",
       " 'employmentTitle',\n",
       " 'annualIncome',\n",
       " 'purpose',\n",
       " 'postCode',\n",
       " 'regionCode',\n",
       " 'dti',\n",
       " 'delinquency_2years',\n",
       " 'ficoRangeLow',\n",
       " 'ficoRangeHigh',\n",
       " 'openAcc',\n",
       " 'pubRec',\n",
       " 'pubRecBankruptcies',\n",
       " 'revolBal',\n",
       " 'revolUtil',\n",
       " 'totalAcc',\n",
       " 'title',\n",
       " 'n0',\n",
       " 'n1',\n",
       " 'n2',\n",
       " 'n3',\n",
       " 'n4',\n",
       " 'n5',\n",
       " 'n6',\n",
       " 'n7',\n",
       " 'n8',\n",
       " 'n9',\n",
       " 'n10',\n",
       " 'n13',\n",
       " 'n14']"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "numerical_serial_fea"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['term',\n",
       " 'homeOwnership',\n",
       " 'verificationStatus',\n",
       " 'isDefault',\n",
       " 'initialListStatus',\n",
       " 'applicationType',\n",
       " 'policyCode',\n",
       " 'n11',\n",
       " 'n12']"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "numerical_noserial_fea"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "数值类别型变量分析"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "3    606902\n",
       "5    193098\n",
       "Name: term, dtype: int64"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_train['term'].value_counts()#离散型变量"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    395732\n",
       "1    317660\n",
       "2     86309\n",
       "3       185\n",
       "5        81\n",
       "4        33\n",
       "Name: homeOwnership, dtype: int64"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_train['homeOwnership'].value_counts()#离散型变量"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1    309810\n",
       "2    248968\n",
       "0    241222\n",
       "Name: verificationStatus, dtype: int64"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_train['verificationStatus'].value_counts()#离散型变量"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    466438\n",
       "1    333562\n",
       "Name: initialListStatus, dtype: int64"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_train['initialListStatus'].value_counts()#离散型变量"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    784586\n",
       "1     15414\n",
       "Name: applicationType, dtype: int64"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_train['applicationType'].value_counts()#离散型变量"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1.0    800000\n",
       "Name: policyCode, dtype: int64"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_train['policyCode'].value_counts()#离散型变量，无用，全部一个值"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.0    729682\n",
       "1.0       540\n",
       "2.0        24\n",
       "4.0         1\n",
       "3.0         1\n",
       "Name: n11, dtype: int64"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_train['n11'].value_counts()#离散型变量，相差悬殊，用不用再分析"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.0    757315\n",
       "1.0      2281\n",
       "2.0       115\n",
       "3.0        16\n",
       "4.0         3\n",
       "Name: n12, dtype: int64"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_train['n12'].value_counts()#离散型变量，相差悬殊，用不用再分析"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "数值连续型变量分析"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x3672 with 33 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#每个数字特征得分布可视化\n",
    "f = pd.melt(data_train, value_vars=numerical_serial_fea)\n",
    "g = sns.FacetGrid(f, col=\"variable\", col_wrap=2, sharex=False, sharey=False) \n",
    "g = g.map(sns.distplot, \"value\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "查看某一个数值型变量的分布，查看变量是否符合正态分布，如果不符合正太分布的变量可以log化后再观察 下是否符合正态分布。\n",
    "如果想统一处理一批数据变标准化 必须把这些之前已经正态化的数据提出"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'Probability')"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAA9EAAAGeCAYAAACToYLjAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADl0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uIDMuMC4yLCBodHRwOi8vbWF0cGxvdGxpYi5vcmcvOIA7rQAAIABJREFUeJzs3XecZXV9+P/Xe9o22AKsosAKKhaMBUPUaGKJDbGAsaGxoChp+rUbjcagv5ho1GiKNRbUBA1qVBJRNHZFUaSogCjSi5Rt7O7M7MzOvH9/fM7dvXv33plzp9zZHV7Px+M+5s45n/M5n3tuOed9Pi0yE0mSJEmSNL2+hS6AJEmSJEn7CoNoSZIkSZJqMoiWJEmSJKkmg2hJkiRJkmoyiJYkSZIkqSaDaEmSJEmSajKIlqQuRETO4HHaQpd7sYmIW6tje9BCl6VZRAxGxE1V2Z5eI31ExBVV+pNnue8vVvmcMJt89hYR8Yo236XtEXFLRFwUEadFxLMjYskUeby32u4VvSx7h7Ksrsqyqc26TdW61QtRtlYR8YCqPBcudFkkaW80sNAFkKR9zCfaLDsYeDywDfhcm/Xfn9cSLTIR8S7g1cBrM/NdC12ebmTmeET8B/Aq4CTafx6aPRI4gvLZ+a95Ldy+61rgm9XzfmAVcC/g+cALgJsi4s8y84vzVYAqmLw/cHRm7vOB5WJ7PZLUawbRktSFzDypdVlEPJISRN/abr3mxUMo57CNC12QNj5GCaKPjYiDM/O3U6R9YfX3s5m5df6Ltk86v8P37gjgbyjH8AsR8fzM/FRLsr8HPgjcNO+lnN5twL2BiYUuSA2XUso6utAFkaS9kc25JUn7nMy8PDN/mZl7XUCSmRcDP6bUmj6vU7qI2B94WvXvx3pQtEUlM6/MzBcBb64WfTgi7tSS5ubqc7LgN1syc7Iqy68XuizTycztVVmvWuiySNLeyCBaknokIl5a9TP8t4i4Y0R8ICKujoixqglwo4/ssyLiExFxaURsjoiRiLgsIv65NUhoyvu8Ku9jIuKhEXFWRGyotj0/Iv6kw3YHRcS7IuKXVdqRiLg2Ir4REa9sSTujslXb9kXEcyPia1Wf1u0RcV31/ylVmv0iIilNuQHe2dIf9jVN+XXsEx0RKyPiLRHx84jYFhFbIuKnEfGaiFjaJv2Tqrz+NyKWVtv+uirjb6u+tx1fWweNoPikKdI8C1gO/Dozv9dyrE6MiE+1Oc7viYg7dlOQmKav9HT9hiPiERHxuYi4ofqs3hQRn4+IYzqkv19EnF59jsYi4rYo/b4/GxFP7KbsNf0d8GtgKfCXLWVp+9qqz/ILI+J7EbExIsarz+WF1Wf50CrdCdVn8v7Vphe0fCYf0JyuOtYrI+Kd1WdoNCK+XaXp2Ce6pWzPi4gfR8TWqmz/GxG/2ybdtPlFS1/rLl7PlH2iI+LuEfGRKL9f26P81nw9Ip7aIf3O9yEiDqu+UzdW214eEadGxOBUx0WS9iY255ak3rszcD4wBHwPmARuqdYtAT4DbAEuAX4OrACOBv4f8MyIeHBmXtMh7z8GXldtdzalv+2Dgf+IiP0y80ONhBGxCvgRcDfgBuBrwEhVvgdQLrTf05T3jMoWEcuBLwKPBcaBHwLXU/qSHw08FPhwte4TwDHAfYDzgIubsvpFh9fcvK87A98C7gGsB75COdc9Cngn8IyIeExmbmmz+VLgG8DvAN+p9v1QSr/bh0XE0V00uf405dgdFREPyswft0nTaMr98Zbly6vtb6M0q20c5wcCr2DXcb6uZllmLCLeSmkyPUl5P74PHE75nD0lIp6bmf/VlP4hlOO/lPJ+nQsEcCjwFEpT5i/PZRkzMyPiP4FTKZ+xN9XY7D3Ay4HtwA8ozb0PAO5K+Sx/BbgOuIbymXwKsAb4H2BDUz7NzwFWUj7fhwDfBS6o9lHX31blOqfa132BJwKPjYjjM/OrXeTVTrevZw8R8WjgS5TP5K+A/wbuSPmOPSYi/i0zX9Zh83tQfvuGKcfnQOAPKK/7bkzRckOS9iqZ6cOHDx8+ZvGgDA6VwFXTpHtplS6BLwDL26QZAJ4OLG1ZPgT8U7XtZ9tsd161bgJ4Vsu6P6vW3QwMNi3/i2r5GUBfyzaDwKPmqGwfqdb9DLhrm/08qWXZu6r0r5niWN5apTmoZflZ1fKzgf2blq8Fflqt+/eWbZ7U9L58Hzigad2BlGA6gZd3+bn4VLXdB9qsO7JatwO4c5vj+TRgSZvl/1xt9+k2eX6xWndCneVN699brX9Fy/ITq+W/Ae7fsu6xlBsu24BDmpb/d7XNn7fZz2rgQV0cv1dUeX2xRtonVmm3TvfaKMHyDsqNq3Vt8jqq+TVVyy6s8nlAh/2f0PIZWtPh9Sewqc26TdW6MeC4lnWvZ9f3d1Wd/Nrku7rL1/OAav2FLctXVcctgbcA0bTuQU37a/0NarwPSfmt6G9a97uUGw0J3Keb75gPHz58LNTD5tyS1HsjlCBjuHVFZu7IzM9l5mjL8jHgNZSL1CdHxFCHvD+VTTWDlQ9RaqDWUmq2GhrNgr+WmZMt+xvPzG/NtmwRcRdKjes4JYi7os1+/rfDa+lKRNwbeEK1r5dkU21zZt4C/Gn17wui/dRYO4CTMnND03brgXdX/z66yyI1mnSfGHs2I2/UQp+dmTc0r8jMscz8fGZub11OGbBsC3B8RMx3a7K3VH+fm5kXtZTl65Tjshx4UdOqxmfqK62ZZeambF8jPxdurf6uiCmmvKocSOmvfnG2adGRmZdk5vUzLEcCf5Yz74P9ycw8q6U8bwcuonx/nzvDfOfK84GDKK0MTs3MbKyo3tu3V/++ps22AL8EXpdNYxlk5k+Bz1f/dvsdk6QFYXNuSeq9c3LqEZuJiKOAx1GaOK5g1xgWk5Rm1Xeh9ANttUdAmpkZEZcB69jVlBzK4FcAb46IrcBZmXnbdIXvsmyPrdZ/vTWAngePqP5+q0NwdF5E/JxyI+FhlCapzS7LzMvb5PvL6u+duyzPt4ErKE2ET6A0hSci+ijBCEwxoFhE3IdynO/K7sd5AtgfOAy4sssy1RIRd6M0vb0+M3/YIdl3gDcCv9+07MeUJvAfj4i3AD/IzPH5KGOL5kqByY6piispQffDI+L/A07LzN/MUTl+lZnTdjuYwn9Msfz+lFYv75tF/rPV+I59sjmAbvIx4B+AB0bE/rlnt4mzM3NHm+1m+h2TpAVhEC1JvXd1pxVVLe5Hmb7GaWWH5Z36SjeC4501opn55Yh4H6VZ96eByYi4lNJP+7OZ+c3mDGZYtrtUf3/ZLuEcO6T6O1VgeQUliD6kzbrax66O6ubFacBbKQOMfaZa9bhq/7cCZ7ZuV9Wkfgx4zjS76PQZmAt3rf4eUg1ENZW1Tc/fQumD/8jqMRoR51P6Sf9HZs7X56DRsmDrdEF7Zu6IiOcBp1P6T78pIn5L6cv8VeA/M3PbDMvR8btdU6fP7lXV30Nnmf9sTfkdy8ybI2Ib5abPnSitJprN6XdMkhaKzbklqfdGplj3BkqQejWl//FhlL6xkZlBGWQKymBN7UxXC7ebzHwpcE9K88svAXeg9KH+RkR8oao1nU3ZpgvA5sNM99nVsavptCrfx0ZEIwBpNOX+jw4B35soAfSVlL7Rh7L7cb60StfpM9CtdtcC/dXfWygDUU312Nl0u2qy/VDg4ZRRs39I6V/7RuDi1lGy51Bj9OqfT5mqkmWArrsAf0IZ1G498FRK14dfR8Q9Z1iOqb7bC2G+rvP2pu+YJPWcNdGStHd5RvX3pMz8dvOKiAhKE+o5lWXe2ncD76728ShKzfQJlMGlTp9F2Ro1TzMNSrrR6Md61ynSNNbNtM9rVzLz2oj4P0rt8/Mj4oPA8dXqTk25G8f5+Zn5/eYV1U2NI7osxlj1d78O6+/SZtm11d/NmXlSl/sjy5Rd3wOo+oOfDPwrZdqyM1r7gc9G9dlr1Np/vYsybqF8tk+v8llHaSr9JMro3cfNVRm7cDjta7MPr/42f24b7+vyiOhrHdcgItZQmv3PpSm/YxFxB0ot9CRw4xzvW5L2GtZES9Le5YDq77Vt1p1AGchp3mTxTXYFzvdvWj2Tsn2dckH96Ig4vGYxGsFBtzd6v1P9fWREHNa6sppr976Ugcd+0GXes9E8Z/RzKP3Gz8vMTrWmUx3np9F9k9dG4HOv1hXVNGcPbbPNJZQbIHePiKO73N9uMnM0M99HGeV8gDJ92Vx6E2W082Fm0V+46kd/avXv/VtWz/Qz2a2287mz6ybBtxsLqoEJN1FGuG8X1E51E2C237HnVTcvWjVaWZzfpj+0JC0aBtGStHdp9Bn9i+aL1Grk6X+Zyx1FxDMj4vdbL4YjYn9Kf1bYvVas67Jl5tWUJr+DwBdbA+mIGIyIJ7Vs1gj67l37xZR9XUrp0zoEfCgidta8VqNxf6D69xOZeWubLObLFynz796DMh8uTDGgGE3HuXlhNdDYe2ew/29Uf19SjZbeyG9/Sh/3PUYqrwaNenP172cj4uGtaSJiICKOjYgHNC17eUTsEdBVg9E1WirMtt9wI88jIuKjlD7nCbw4M2+usd29IuJ5EbGizeondyjjjD6TM/CCiHh884KIeC1lPvX17DnwWOO9PTUi+pu2OYYyL3onM309n6T05b8vpS958+/AMZTpuKBMUydJi5bNuSVp7/J3lP6krwKOrUaTPqha9n+UC9gHdN68K4+jNLO9KSIuoFykrwb+gDIf7EWUAHi2ZXsZpcnwHwG/iohzKBfxBwP3A5axe1PjL1Pmkn1eVaN8FaU2+4zM/No0r+lkyiBWTwCuiIjvUM51f0QZiOvHVfl7JjO3R8TplHnC1wKjlObynfwdpZ/x6yLiiZR+vnegHOevUt6n+3befA9nAd+ttv9ZRHyf0p/69ygDOn0aeHabcn8iIo6gBNPfiYhLKKOuj1BGUX4A5Zg+mzLvMMArgfdGxK8otdnDlMGoHkZ5Hz6Ymb/qouxQRno+rXreX+3znpSbEgH8FvjTzNxjkLYODqYEgx+uPvdXV2W7b5XvKPDXLdt8gdLa4oMR8ceU9wDgLZnZrsXATL0f+EpE/IDSEuG+wO9QWk+8IDM3taR/K6XG+U+AB0fEhZQ+9MdQ+nc/l/JdbjWj15OZmyPiRMr4CW8FnlMdwztSRu7uB/6tzTR7krSoWBMtSXuRqin17wNnUwKuJ1MuUN9M6Us70Xnrrn2IUmN0JaX56jMoAzRdQgn4Hto8SvFMy1bl8XhKgHtOta+nU4KgnwIvb0l/VZXf96vynFRte7/pXlDV1/ZBlAv8m4EnUm4W/AZ4HfCIBWpm2lzz/N9tgqGdqhsFDwW+Rgmen0I53m+kDH7V7eBxk5R+vu8FNlOmHbsf8FnKsepYe5uZpwIPAT5Faa5/LCVoO5hy4+QkSpDe8BpK7fZ24A8pzc8Pr17LUzLzz7spe+Uw4AXV45mUY7OdEgifCBzeRQAN5abEa6vy35HyOX485fP7r8B9W/v8Z+Ynq9d2JeUYnFw9DpzB65nKW6p8l1O+A4dRju/DMvPLrYkz82eU4/xVymfliZTuAn9eDRrY1mxeT2Z+g1Iz/jFK/+enAw+kNDV/Wma+rN5LlaR9V7Sf5k+SJEmSJLWyJlqSJEmSpJoMoiVJkiRJqskgWpIkSZKkmgyiJUmSJEmqySBakiRJkqSaDKIlSZIkSarJIFqSJEmSpJoMoiVJkiRJqskgWpIkSZKkmgyiJUmSJEmqySBakiRJkqSaDKIlSZIkSarJIFqSJEmSpJoMoiVJkiRJqskgWpIkSZKkmgyiJUmSJEmqySBakiRJkqSaDKIlSZIkSarJIFqSJEmSpJoMoiVJkiRJqskgWpIkSZKkmgyiJUmSJEmqySBakiRJkqSaDKIlSZIkSarJIFqSJEmSpJoMoiVJkiRJqskgWpIkSZKkmgyiJUmSJEmqySBakiRJkqSaDKIlSZIkSarJIFqSJEmSpJoMoiVJkiRJqskgWpIkSZKkmgyiJUmSJEmqySBakiRJkqSaDKIlSZIkSarJIFqSJEmSpJoMoiVJkiRJqskgWpIkSZKkmgyiJUmSJEmqySBakiRJkqSaDKIlSZIkSarJIFqSJEmSpJoMoiVJkiRJqskgWpIkSZKkmgyiJUmSJEmqySBakiRJkqSaDKIlSZIkSarJIFqSJEmSpJoMoiVJkiRJqskgWvu0iHhkRGREnLTQZdHUIuLbEXHVQu9zPsvRbd4RcVpE5HyURZJaec5cOBHxjoi4MiKGFrosDRFxfESMRcSRPdhXz8937fY5n+XoNu+IOLX6Ph4+H+XR/DKIlnogIv68+qG8LSKWL3R5GqoLqlMjYnUX25xWvZbGYzQiboqI70bE2yLirnNcxgdUZTx8LvPtlYg4KSJesdDlkKR9xWI6Z1bbHQG8HHhrZo41LW+cTw+a67LWkZlfAn4OvKPuNk2BX+MxFhG3RMSPIuI9EXG/uSxjRBxe7fMBc5lvr0TECRFx6kKXQ3PPIFrqjZOB3wD7A89Y4LI0eyTwt0BXFwSVPweeB/wZ8E7gt8CrgUsj4lVt0j8OuOcM9vOAqoyHz2Dbme5zptrt7ySgUxD9EmDZfBZIkvZBi+2c+XrgNuA/5rpAc+CfgadGxH263O7NlGuAlwBvA35Jed8ujIh3tUk/0/Pd4ZRjPpMgutfn2Hb7O4FS/nb+rkp/9XwWSvNjYKELIC12EXF/4HeB5wOvBF4EfGJBCzU3PpeZtzYviIh1wP8C746I6zPzvxrrmu++z6eI6AeWZOZwr/bZ0O3+MnMcGJ+n4kjSPmexnTMjYiXwJ8BHq9/8vc1/Ax+g3BB/WRfbfSUzz2teUN1A/yzw6oi4JTN31nD36nwXEQGsyMytvT7Hdru/zNwB7Ji/Emk+WROtRSkiVkTEP0TEbyJie0T8NiI+GRF3aUnXFxFvrJoi/7ZqlnRNRHwgIg5sSXt41XTp1Ih4UkT8pGrKfGNEvDMiOt2UOhnYSjlRnQY8PCLu3qbMJ1X5Pzoi3hwRV0fESEScGxEPqdI8IiK+HxHbqv3+TZt8rqr65t4rIr4cEVsiYnNEfC4iDm5Kdxq77o5e2dQ069S6x7lVZl4DPB2YpNyZbi5Xu/7J94mIz0bE9U3v07ci4onV+lOBj1fJv9VUxtNajtljIuJvIuI3wCjwzE77bNr3XSPiS9WxuS0ivtDaFL0p/0e22X7a/tbV80cAd2lp/vbIan3b/lMRcb+qPOurz9glEfG66gZBc7pGU8BV1Wf25ir9DyLiwe1etyS18pw5r+fM44AVwFnTpJtSRDw8Ir5elW0kIs6PiJM7pH1aRFxUHe9rIuJvq/PkHv3hM3Mr8D3KuXtWMnMDpeXAbcAbImJFU5na9U8+LCI+Vr1326tz2DkR8YJq/UnAt6rkH2865t+u1u/s4x8RfxkRl1CuAV7TaZ9N+15bfcbXV5+Pb0TEA1vSdBxDoMPr2W1ZVc7Ga2m+BjipWta2T3T13flUlK5y26vv5d9HS9eGpu3vWa2/rkp/UUQc1+51a+5YE61FJyIGgbOBhwGfA94NHElpfvy4iDgmM6+rkg8BrwU+D3wJ2Ab8HuUk/gcR8bttahePA/4C+CDwMeB4yg/2RuDvW8qyhHIH+nOZuS0iTgfeRbmz/tcdXsLbgX5KE6shShPpr0XE84GPAh8G/pMSKL41Iq7MzNYmYocA3wa+UL2++wN/CqykNDkG+FD1/1Mpd/sbtco/61CuWjLzVxHxPeAREXHPzLysXbrqguub1b8fpDRnOgg4Bngw8GXKRdSdgFMox/bSKv1vWrJ7FzAI/Dvl5N12n01WUI7PucAbKJ+PvwAeEhFHZ+Zva73Y6b0C+AfK63pl0/JL2yeHiDgG+A7lbvb7KM3kn0zps3Z/yuep1dnALcBbgQOBVwFfjogjMnPL7F+GpMXKcyYwv+fMR1R/fzJNuo4i4slV2X5LeX+2ACcCH4mIu2bmG5vSPgv4NOU8+RZKTecLKOeRTn4IPD4i7pWZv5xpOaEE0hHxhWqff0D5bLV7TQPA1ynH/v3Ar4BVwP2AP6S0Pvgu5TPy15T38XvV5je1ZPcKyrnv3ynH6NoaRf0qsAE4FTgYeCnwnYj4/cz8RY3t63gbpcLyDylN3xvO6bRBlBtXP6Yci/cDv6Z0I3gD8LCIeHRVg93sE5RrhndRvgOvAL4YEffIzKvm5JVoT5npw8c++6D8sCRwUtOyl1TL/rEl7ROr5Z9qWhbAsjb5nlylfWbTssOrZduAw1vy+AVwY5t8nlVt88imZV8Argf6W9KeVKU9HxhqWv6Uavk4cEzT8iHgRuCHLflc1Vr2avn7quX3bFp2arXs8NayT3HMT6u2OWiKNP9SpXly07JvA1e1eV3PnGZ/jePyyCnWXQYsb7N+t302LUvgvS3Ln1ot/2DNfXfKe9plrceyZdkPKBc992v5jJ1RleXRbd6L97fk8Yxq+Z/O5/fPhw8f+9YDz5kLcc78DrChw7rGb/hU59N+yk3mTcCdW17PD4AJ4Mhq2UB1rG4C1jSl3Q+4ovW9b1r/3Grd02q8nsYxOGaKNK+q0rys9bU2/X+/Ks3ruv3Mtlm3AbhDp+Pb4Zj/NxBNy3+X0oruqzX33THv6ZZN9Xmi3PBJ4LiWtO+slp/cZvv/bXktv1ct/4e6n1Mf3T9szq3F6KmUH8J/aF6YmV8GLgSOj4i+allm5giUvrQRsTrKKJmNGtJ2TWK/mE139rL8Yn0LODgi9mtJezLlBP2dpmWnAXcGju1Q/g/k7nfyG3dez82m/kdVmh9Tagxa3ZCZZ7Qsa7ymeZ/KglIbDOWufSebq79PiNJnbDY+kJnDXW7z9uZ/MvMLlGD8hFmWZcYi4g7AQ4EzM3Nn7Ub1GWs0j39qm03f0/J/L99rSfs2z5nze85cSwnyZup3gXXAxzLzhsbC6vX8I6Wm8/imtHcGTsvMjU1pt1JaAnSyvvp7h1mUs1k31wCPqs59s/HJzLy5y23+sfosApCZP6XUjD+mzeeyJ6rv2VOACzKztfn/P1C+p+2uAf655bX8hNIlwmuAeWQQrcXoCMoJcWObdRdTRvvcOZ1ERDwzIs4FRijNy26h3LEFWNMmjyvaLGucgHb2Caua5Dwa+Bpwt4i4e5R+Xb+iNMVq25epNf+m13Flm7Qbm/fZbRnnUePEeVunBJn5HeCTlNqEW6P0431LRBw1g/39qsv0m7J9k+1LgTs29+PqsSOqvxe3WXcp5QTabgqx1s9ML99rSfs2z5nze85MSu37TE11Xmgsu2tL2nZdmqbq5tQoX06Rpht1rgGuptwcfhxwY0T8NCL+MSJ+bwb76/YaANp3q7qEUvN/lxnkNxfWUloN7PFeZ+lvfiM1rgEq6/EaYF4ZROt2LSL+GGiMIP1ySp+hx7Lrjne778jEVFk2PX9htf0plD4tjccllIuSJ0XE2i7yn2q/My3jfGnMEzll3+TMfAFwX+CNlB/8VwM/i4iXdrm/bmuh65rqgmKvGVMiMzu93714ryXdTnjOnJFbgANmmcd8a5TvljnKr+41wJsotaWvoPThfjHw44ioPW915XZ9DUDnz6/XAPNob/oASHPlCuDYiFidmZta1h1FuTPaGBDkeZSRHB/V3Bw4Iu41mwJERFBqWC+kZZTqysHAv1Km8Hj3bPY1S3N113mniLgHZRCNX2fmtHeHswzg8QvgnRGxmjLY19sj4n1V86Q5LyOwOiIOblMbfW/g5szcVv3faILX7gLoCOpNZdFN+Rs1J+3m67wX5QKz3R1nSZopz5n1zeR89AvKQJsHZcu0kDU1fvPbnReOaklzVfX3nm3StlvW0Bj9fNYDakXEAZQmx5uB70+XPjOvoLy3/xoRSykDkb0uIt5dNdGej2sAKOf7H7UsO4oSkDbmbZ7qGqBdjXA73ZT/Fkqriz3e64hYQxlo9cIu8tM8siZai9EXKZ/t1zcvjIgnAEdT+ptOVosnKD9wfU3pAnjTLMvwGEpzoE9l5ufaPP6NcrJ70Sz3M1tbq79zcpc8yjzRn6UczzdOk/aARj+7huoC7kpgObB0PsrYpPXz8VTKRcYXmxY3bgI8piXtsyn9zurYCqypPldTqi4YzgGeHBG/07S/oIzMCWWQHUmaK54z65vJ+ejb1d+HzHCf5wPXAC+M3afcGqSMJJ6UkdIBzqM0+T2pCroaafejzAPdyUOAm7LDbBp1VQH0ZynNud821VglUaZmHGxelpmj7Gpm3Sj/fF0DvK75vBxleqvHAN+o+pBDuR7ZwZ7XAA+l/vu5tdpm2vJX37P/AY6OiNYxAF5P+d55DbCXsCZai9FplKkV/irK3Hvfpdxl/QvKiJXN02R8Dnga8M2I+CRlmqQTKEHcbDT6bv33FGk+D7w6Ih6Sma13Q3ulsd93RMR/UmoYfpH1pnd4ekRspfyOHAg8iDIgRh/wisz87DTbPx94ZTUVxuWUWt1HAI8HzmgMXkOZFmQSeGN1UbANuDIzz637Itu4FfjjiLgz5QKnMcXVTZTRLgHIzMsi4v+AP61OthcCD6DcZb+c8nmZzo+AJwH/FhHnUC5CvznFICgvpwyq872IaExx9STKcTk9M7/R3UuVpCmdhufMumZyzvwqpXbxOMooyu28KiLaBZzfzMxzqi5OXwB+EhEfrvJ7FiWQ+/vM/DVAZu6IiNdQRnj+cUR8lBIEnkTpMnUELTWjVYD9h5Tpx7rxhKoFQh8l4D2acm7cH3hnZr5zmu0fBXw4Ij5Pafa9lTIw2ospg8I1AvpLqtf7F9Ux2kRpMfbNNnl24y7A2RFxJqWG96WUfv6vbSTIzK1R5gd/cUR8ml3XCy+kTG12/xr7+VGV9/sj4suUa51zM7Ndn30o37fHUqaoej/lWuPhlPf7u5TprLQXMIjWopOZ4xHxeMqd8WcBf0z50f0s8KbMvLYp7WciYn/KnI/vogw68j+UO37rW/Ouo7rbeAJwfk49P9/nKX2AX8SeTYp6IjN/EBF/RblD/e+U34S3UK9J1weqv2OUZluXUZrZfaxqnjWdb1NOuk+inMAmKHd9XwP8W1MZr4mIFwF/Ve1zkHJdYKhJAAAgAElEQVQSmU0QvQ34I8qo1m+n9Bv6KvDqzLyxJe3zKE3N/qR6/j3Kyf8DlClcpvMeSrOvp1OOc1+1fdsgOjPPq+5yv4VyEbuC0lTvr1jYZoySFiHPmfXN5JxZBWL/ATwrIl6Re86jDbtaGrXaAZyTmf8TEY+mvEevpUxvdSnw4sz8aMv+To+IceBvqrLdRJkv+2eUmxQj7O5plJsgH+r8ytt6a/V3nNLk/wpKIP7x5tklpnBRVZ5HUs6v/ZQa97+n6VyXmSMRcSLwd8B7gSWUG82zDaKPBf6JcoyWUT5Tr21T9ldSrhGeShkF/aeUsQBOoV4Q/WnKtc6JlOkn+yhBeNsgOjOvjogHU47vc4HVwHWU0bn/LvecI1oLJJpGRJckSZI0h6oa/l8CL83MjyxQGV5NufHx+801+RFxPnBVZv7xQpRL2lcZREuSJEnzKCLeTqmNvEeH2ui52s8QMNE8a0PVZPtnlL7Kd27sPyJOAM4A7tNoEi6pHoNoSZIkaRGo+il/BfgMpcnwnSh93o8A/jwzP7iAxZMWDftES5IkSYvDLZT+vX8C3IHSr/rnwOsz84yFLJi0mFgTLUmSJElSTdZE13TQQQfl4YcfvtDFkCQtEj/96U9vzcy1C12OfZnnZknSXKp7bjaIrunwww/nvPPOW+hiSJIWiYi4eqHLsK/z3CxJmkt1z819810QSZIkSZIWC4NoSZIkSZJqMoiWJEmSJKkmg2hJkiRJkmoyiJYkSZIkqSaDaEmSJEmSajKIliRJkiSpJoNoSZIkSZJqMoiWJEnzKiI+FhE3R8QvOqyPiPiXiLg8In4WEQ/sdRklSarLIFqSJM2304Bjp1j/BODI6nEK8IEelEmSpBkxiJYkSfMqM78LbJgiyfHAJ7P4EbA6Iu7Um9JJktQdg2hJkrTQDgGubfr/umqZJEl7nYGFLoDUa6efe03Hdc958LoelkSS1K2IOIXS5Jt16/zNltSZ13yaL9ZES5KkhXY9cFjT/4dWy/aQmR/OzGMy85i1a9f2pHCSJDUziJYkSQvtTOD51SjdDwE2Z+aNC10oSZLasTm3JEmaVxHxaeCRwEERcR3wt8AgQGZ+EDgLOA64HBgGXrgwJZUkaXoG0ZIkaV5l5rOnWZ/AX/aoOJIkzYrNuSVJkiRJqskgWpIkSZKkmgyiJUmSJEmqySBakiRJkqSaDKIlSZIkSarJIFqSJEmSpJqc4kqSJEmSZun0c6/puO45D17Xw5JovlkTLUmSJElSTQbRkiRJkiTVZBAtSZIkSVJNBtGSJEmSJNVkEC1JkiRJUk0G0ZIkSZIk1WQQLUmSJElSTQbRkiRJkiTVZBAtSZIkSVJNPQ+iI+LYiLgsIi6PiNe3Wb8kIv6rWn9uRBzetO4N1fLLIuLx0+UZES+tlmVEHNS0PCLiX6p1P4uIB87fK5YkSZIkLRY9DaIjoh94H/AE4Cjg2RFxVEuyk4GNmXl34D3AO6ptjwJOBO4DHAu8PyL6p8nzB8BjgKtb9vEE4MjqcQrwgbl8nZIkSZKkxanXNdEPAi7PzCsycwz4DHB8S5rjgU9Uzz8HPDoiolr+mczcnplXApdX+XXMMzMvyMyr2pTjeOCTWfwIWB0Rd5rTVypJkiRJWnR6HUQfAlzb9P911bK2aTJzB7AZOHCKbevkOZNyEBGnRMR5EXHeLbfcMk2WkiRJkqTFzoHFppCZH87MYzLzmLVr1y50cSRJkiRJC6zXQfT1wGFN/x9aLWubJiIGgFXA+im2rZPnTMohSZIkSdJueh1E/wQ4MiKOiIghykBhZ7akORN4QfX86cA3MzOr5SdWo3cfQRkU7Mc182x1JvD8apTuhwCbM/PGuXiBkiRJkqTFa6CXO8vMHRHxUuBsoB/4WGZeHBFvBc7LzDOBjwKfiojLgQ2UoJgq3RnAJcAO4C8zcwLKVFateVbL/x/wOuBg4GcRcVZmvhg4CziOMjjZMPDC3hwBSZIkSdK+rKdBNEBmnkUJYpuXvbnp+SjwjA7bvg14W508q+X/AvxLm+UJ/GW3ZZckSZIk3b45sJgkSZIkSTUZREuSJEmSVJNBtCRJkiRJNRlES5IkSZJUU88HFpMkSZIkzc7p517Tcd1zHryuhyW5/bEmWpIkSZKkmgyiJUmSJEmqySBakiRJkqSaDKIlSZIkSarJIFqSJEmSpJoMoiVJkiRJqskgWpIkSZKkmgyiJUmSJEmqySBakiRJkqSaDKIlSZIkSarJIFqSJEmSpJoMoiVJkiRJqskgWpIkSZKkmgyiJUmSJEmqySBakiRJkqSaDKIlSZIkSarJIFqSJEmSpJoMoiVJkiRJqskgWpIkzbuIODYiLouIyyPi9W3Wr4uIb0XEBRHxs4g4biHKKUnSdAyiJUnSvIqIfuB9wBOAo4BnR8RRLcneBJyRmUcDJwLv720pJS1W51+zkTPOu3ahi6FFxCBakiTNtwcBl2fmFZk5BnwGOL4lTQIrq+ergBt6WD5Ji9h3f3ULF9+weaGLoUVkYKELIEmSFr1DgOZqoOuAB7ekORX4WkS8DFgBPKZdRhFxCnAKwLp16+a8oJIWl5tuG+XmLdsBmMykL2KBS6TFwJpoSZK0N3g2cFpmHgocB3wqIva4TsnMD2fmMZl5zNq1a3teSEn7lp9fv6sGenxicgFLosXEIFqSJM2364HDmv4/tFrW7GTgDIDM/CGwFDioJ6WTtChl5m5B9NgOg2jNDZtzS5Kk+fYT4MiIOIISPJ8IPKclzTXAo4HTIuLelCD6lp6WUtKictNt27lly3YOW7OMazeOMD6RtbY7/dxrOq57zoPtRiJroiVJ0jzLzB3AS4GzgUspo3BfHBFvjYinVMleDbwkIi4CPg2clJn1rnglqY2fX7+JAI5etwawJlpzx5poSZI07zLzLOCslmVvbnp+CfCwXpdL0uLUaMp917UrWLN8CIAx+0RrjlgTLUmSJGlRufTGLdy6dYzfOWQVQwMl5LEmWnPFIFqSJEnSovLln99AAPe58yqG+g2iNbcMoiVJkiQtGpnJl392I3dbux/7LRlgcKDMDW1zbs0Vg2hJkiRJi8alN27hqvXD3PeQVQAsGegHYNyaaM0Rg2hJkiRJi8bV67cBcOgBywB2Nee2JlpzxCBakiRJ0qIxMj4B7Aqebc6tuWYQLUmSJGnRGB4rQfRgNSr3QF8ffeHAYpo7BtGSJEmSFo3RlppogKGBPoNozRmDaEmSJEmLxs6a6OYgur/P5tyaMwbRkiRJkhaNkfEJBvuD/r7YuWyw35pozZ2eB9ERcWxEXBYRl0fE69usXxIR/1WtPzciDm9a94Zq+WUR8fjp8oyII6o8Lq/yHKqWr4uIb0XEBRHxs4g4bn5ftSRJkqReGBmbYNlg/27Llgz0Md7jmuizL/4tX/n5jT3dp3qjp0F0RPQD7wOeABwFPDsijmpJdjKwMTPvDrwHeEe17VHAicB9gGOB90dE/zR5vgN4T5XXxipvgDcBZ2Tm0VWe75+P1ytJkiSpt0bGJlg2tHsQPbgAfaJ/ddMWfnjF+p19tLV49Lom+kHA5Zl5RWaOAZ8Bjm9Jczzwier554BHR0RUyz+Tmdsz80rg8iq/tnlW2/xRlQdVnidUzxNYWT1fBdwwx69TkiRJ0gIYHp9g+dDAbssWok/06PgEOyaTi2/Y3NP9av71Oog+BLi26f/rqmVt02TmDmAzcOAU23ZafiCwqcqjdV+nAs+NiOuAs4CXzeZFSZIkSdo7jIxNsLSlOfdCjM7dmK/6wms39XS/mn+314HFng2clpmHAscBn4qIPY5FRJwSEedFxHm33HJLzwspSZIkqTsj4ztY3tKcu9c10ZOZbB+fZKi/jytu2cZNt432bN+af70Ooq8HDmv6/9BqWds0ETFAaW69foptOy1fD6yu8mjd18nAGQCZ+UNgKXBQa2Ez88OZeUxmHrN27dquXqgkSZKk3ms3sFiv+0RvH58kgQcctpoE/ucie48uJr0Oon8CHFmNmj1EGdTrzJY0ZwIvqJ4/HfhmZma1/MRq9O4jgCOBH3fKs9rmW1UeVHl+qXp+DfBogIi4NyWItqpZkiRJ2scNtxlYbEl/b0fnbjTlPuyA5RyyehlfutAgejHpaRBd9U9+KXA2cCllhOyLI+KtEfGUKtlHgQMj4nLgVcDrq20vptQeXwJ8FfjLzJzolGeV118Br6ryOrDKG+DVwEsi4iLg08BJVdAtSZIkaR82Ot6+Jnp8Ipns0SV/I4heNtjH/Q9dxc+v38xvbtnak31r/g1Mn2RuZeZZlMG8mpe9uen5KPCMDtu+DXhbnTyr5VdQRu9uXX4J8LBuyy5JkiRp7zY8NtG2TzTA+MQkSwb62202pxrTWi0d6ud+a1bzlYt/y5cuuJ5XPe6e875vzb+eB9HSvuj0c6/puO45D17Xw5JIkiRpKiPj7UfnBhjb0ZsgemSsURPdz8plgzz0bgfypYtu4JWPvQdlJl7ty26vo3NLkiRJWoRGpqiJ7tXgYqPju4JogOPvfwhXrx92uqtFwiBakiRJ0qIwPjHJjsls2yca6Nk0VyMtQfTjf+dgAM75zfqe7F/zyyBakiRJ0qIw3GhG3To6dxVEj/eoJnpkbIK+2NWMfNWyQZYP9bNx21hP9q/5ZRAtSZIkaVHY2Yy6JYgebDTnnujd6NxLB/t36/+8etkgG4fHe7J/zS+DaEmSJEmLQqMmeo8+0QO97RPdbnCzVcuH2DxiTfRiYBAtSZIkaVFoHhW72c6BxXrUJ7rdXNWrlw2yaQ5qos+/ZiNP/8A5bN8xMeu8NDNOcSXtZZxOS5IkaWZGxncAsGxoALbtClh7XhM91iaIXj7Ir2/eOuu8z7tqA+ddvZH73Hkl9zx45azzU/esiZYkSZK0KIyMlSB54WuiJ1k6tGcQPRc10RuqmwNX3LJt1nlpZgyidbuSmWwcti+KJEnSYjQ8VmqiW/tEDw6UAb562Sd62eDuodaqZaVPdObsBjfbVF3LXnGrQfRCsTm3blfOvvgm3nX2ZbzmcfdkzYqhhS6OJEmS5lBjfubWQb0G+vroj2B8AftEr1k+yPhEMjw2wYolMw/DNlTTZN2waaQ0G2+5YTAduw7OnkG0bld++JtbSWD9tjGD6Fnwx1eSJO2NRjqMzg2lNroXNdHjE5PsmMw9AvnVywcB2DQyPqsgeuPwGMsG+xkZn+Cq9du4953sF91rNufW7cr512wCYMuoc/RJkiQtNo2a6NZaYCj9onvRJ3qkw1zVq5aVCpyN22bXtXDj8DgPu/uBDPQFV9qke0EYROt2Y2RsgktvvA2A20Z3LHBpJEmSNNca80S3a+I8NNDXk5roRm14p5rozSOzq8zZuG2MO65cymEHLOeKW2Y/2re6ZxCt242fX7+ZHZNlIIfbrImWJEladEbHJ4iAJQN7hjlD/b0Jokc71IbvbM49ixG6JyfLILkHrBjirmtXcOPm0Z2Dqal3DKJ1u3HBNRsBWDHUz5ZZ3gGUJEnS3md4bILlg/1ExB7rBgd63Jy7NYiumnNvGpl5c+7bRseZTFizfIi7HrQfCVx16/CM89PMdBVER0R3Q79Je5Hzr9nIXQ5czh1XLWWLzbklqTbP/5L2FSPjnUerXjLQ15PRueezJnpjte0BK4Y4bM0yBvqCK261SXevdVsTfX1E/GNE3HteSiPNk8zk/Gs28cB1a1i5dNDm3JLUHc//kvYJU035NNij5tw7+0S3lGPpYD9LB/tm1Se6Mb3V6uWDDPT3cZcDlzu42ALoNoj+IPB04BcRcW5EnBIRjqmuvd71m0a4Zct2jl63mpVLB9gyumPWE91L0u2I539J+4SRsT3nZ27o3ejcZR9LB/cMtVYvG2LT8MybczdG9j6gmqr1iIP2K/2it9vKspe6CqIz89TMvCvwWOAy4J+AGyPiPyPiMfNRQGkuXFBNbfXAdWvYf+kgOyZzZ38VSdLUPP9L2lcMj0+wbKj9HMy9Gp17dHyCwf5goK9NEL18cGeT7JnYUAXga5aXIPpua1cAcIW10T01o4HFMvObmfl84GDgZcA9gbMj4qqIODUi7jyXhZRm6/xrNrJ0sI97Hrw/+y8tP6xOcyVJ3fH8L2lvNzo2wbI2NcDQu9G5R8Y714avWjbI5lkE0Y1a7DVVTfQha5Yx2O980b0229G5jwEeDtwL2Ah8D3gxcHlEPHeWeUtz5oJrNnG/Q1cz2N/HyqVlUAdH6JakGfP8L2mvNDy+g+UdaqIHB/rYMZlMznOXvqn6Za9ePjir0bk3bBtnqL+PFVX+A319rDtgOVdvMIjupa6D6Ii4S0T8bUT8BvgGcCfgRcCdM/N5wF2ADwHvnNOSSjM0Oj7BxTds5uh1qwFYuawE0dZES1J9nv8l7Qum6hPdmDt6fJ5ro0fHJ1jaoQylT/QsRufeNsaaFYO7TeG1atkgw9vtpthL7W/TdBAR3wL+ELge+Djw8cy8ujlNZk5ExOnAy+eslNIsXHzDbYxPJA9ctwZgZ3PuLY7QLUm1eP6XtK+YbnRuYN4HFxsZn2BVVWnTavWKQTaNjJOZbeeyns7G4bGd/aEblgz0M7rDILqXugqigZuB44Cv59RDG18IHDHjUklz6IJrNgLsrIke7O9j2WC/01xJUn2e/yXtE6bqjzxU1UTPd7/o0fEJDl65tO261cuGGNsxyej4ZMdgfyptg+jBPraPT844MFf3um3O/T7gnHYn0IjYLyIeDpCZ4613qKWFcsE1mzh0zTLusP+uH7P9lw5w24jNuSWpJs//kvYJw2MTLO8QnA7VqIkeGSvdAMdnUVs9Mj6xxxzRDauXlxrqmfaL3rBtbOf0Vg1LB/pJ5r+GXbt0G0R/Cziqw7p7VuulvcoF12zk6Kopd8PKZYM255ak+jz/S9rrTU4m23dMduyPPFSjT/SZF13Pf557De/+2mX85MoNTEx2NwjZZGapZe7YJ7oKomfYL3rj8DhrVuzeVHxJNRr56LhBdK90G0RP1T5gP2B4FmWR5tym4TFu2DzK/Q9dtdvylUsH2OLAYpJUl+d/SXu9kfHSL7hTTXSjT/T2KWpsb9myHSiDdX3hwut57//9it/csrV2GbZXgWzHKa6qmuiNw93XRE9OJpvaNOdeOtBf7dt+0b0ybZ/oqonWI5sWvTgijm1JthR4IvDzuSuaNHuNH8I7tPRL2X/pIFtGdzCZSZ99RyRpD3N9/q+2/WegH/hIZr69TZpnAqcCCVyUmc+ZUeEl3S41guhOfY3r1ERvHC5TSP3ZI+7GL3+7hf/52Q2cedENvPIx9+iqDFONzg3MaK7o20bHmUz2DKKrmujtPZgDW0WdgcUeDLysep7AM4DWKrwx4JfAa+euaNLsrd9W7vId1NJ3ZOXSASYyGR6bYL8l3Y6vJ0m3C3N2/o+Ifkq/6scC1wE/iYgzM/OSpjRHAm8AHpaZGyPiDnPyKiTdboyMVUF0pymuavSJ3jQ8zvKhfiKCe99pJZfdtIVfXL+5fhnGpy7Drj7R3QfRG6rr2tY+0UuqmuhRa6J7ZtroITPfSTXnY0RcCTw1My+c74Jp73X6udd0XPecB6/rYUmmt35r9WOz3+4/NvsvLT9gW0bHDaIlqY05Pv8/CLg8M6+o8vsMcDxwSVOalwDvy8yN1f5vnmnZJd0+TVcTPbhzdO7O/Zw3DY/t1hx82WA/o+MTtUe+bgTyS4fa95pt1CLPpE90own4mtaBxaqAfdSa6J7pqk90Zh5hAK19yYZtpTn3gSuW7LZ8ZTVXtCN0S9L05uD8fwhwbdP/11XLmt0DuEdE/CAiftSm6bgkTakRwM5mdO6Nw2MsH9pVwbJssJ/JrD/y9eg0NdFLB/sYGuib0ejcG7eVwHvN8vYDi9knunfq9Ik+Dvh+Zt5WPZ9SZp41JyWT5sCtVU1064/N/st21URLkva0AOf/AeBISj/sQ4HvRsR9M3NTS7lOAU4BWLdu72r9JGlhDY9N3R+5zjzRm4bHWbFk9yAaSoDeaDY9lemac0cEq5cNzqhP9IZGTXSHgcWsie6dOu1Y/xd4CPDj6nnSeZTOpAwYIu0VNmwbY83yQQb6d290sX/143ibQbQkdTKX5//rgcOa/j+0WtbsOuDczBwHroyIX1GC6p/stqPMDwMfBjjmmGO6m3tG0qI2unN07vYhTn9f0B8xZRC9cXiMtfvvasHYmO95ZHyC1V2UoVMQDaVf9Iyac3fqE21NdM/VCaKPAG5sei7tM9Zv277HDw3AQH8fy4f6uc1priSpk7k8//8EODIijqAEzycCrSNvfxF4NvDxiDiI0rz7ilnuV9LtyPA0A4sBDA5Ex6bZk5PJ5pHxPfpEQ/05mEfGJuiLXbXe7axeNjSz5tzD4wwN9O3RXL0vgqH+PgcW66E6A4td3e65tC9Yv3WMA/db0nbdyqWDbJnByIiSdHswl+f/zNwRES8FzqbUWH8sMy+OiLcC52XmmdW6x0XEJcAE8NrMXD+b/Uq6fZlunmgoI1l3muKqTH/KHn2iYVd/6zplWDrYP+UgZKuWD3LthuFa+TXbWLWwbJf30sE+p7jqoTp9opd3k2Fmdv+JkObJ+m1jHHmH/dquW7lswJpoSepgrs//VZ/ps1qWvbnpeQKvqh6S1LWRsXJd16lPNMBgf1/HmujG6NfNo3s35mAeqVnL2wiip7J62SA/n2Gf6Nb+0A1LBvqtie6hOs25t1L6OtVln2jtNTZsG+PA/dr/2Oy/dJDfbh7tcYkkaZ/h+V/SPqVOTfTQQOc+0Y0gerfm3EPdzcE8Oj4xZXNyKFNUzWx07rG23RSh9Iu2Jrp36gTRL6K7k6hux/amOaQnJpONw2McsKJTc+4Btm7fwWQmfTXm/ZOk2xnP/5L2KdONzg1lmqtONdGNwb6am3M38qpdEz02fRC9atkgo+OTjNaotW62cXiMex28su26pYPWRPdSnT7Rp/WgHNKc2zg8RiYcNEVN9GTCtu072H/pYNs0knR75flf0r5mZHyCJQN99Pd1rhwZGuhj2/b2wWajdri5JrovgiUDfbX7RI+OT7KqQ5PrhtXV1KubR8a7DKLHWbOi/TXrkoE+NjvWT890HjZO2set39p+GoCGlUsb01zZL1qSJGlfNzI2sVt/5nam7BO9raqJbglslw3Vr+UdGZ9g2eDUIdbqZeXatJtpriYmk03DYxzQIUBfOtDvFFc9VGdgsR8DJ2XmJRHxE6Zp2pWZD5qrwkmzsX7bdgAO7NCcu1H7vGVkHFYv61m5JGlf4Plf0r5mZGxijwC41ZKBvo6jc28aHiNi19zQDcsG+2s3567TJ7pRE71puH6/6NtGxpnM0p+6HUfn7q06faIvBkaants/SvuERk10p4HFVi4rP2DWREtSW57/Je1Thscn9giAW009Ovc4q5YN7jFWzrLB/lrNuccnJtkxmbX6RANs6qL5dWPQs46jcw/2s33HpGP99EidPtEvbHp+0mx3GBHHAv9MGcXzI5n59pb1S4BPAr8LrAeelZlXVeveAJxMmT/y/2Xm2VPlGRFHAJ8BDgR+CjwvM8eqdc8ETqVcFFyUmc+Z7WvT3mXDtiqI7nDHbr8lAwRw26j9RySp1Vyf/yVpvo2OTUw5MjeUPtGdRufeNDLeNkhdOtjPrVu3T7v/Rm31dIF8oza5m5ronUF0p5rogdKEfGzHZFf9rDUzM+4THcXamGom8T236QfeBzwBOAp4dkQc1ZLsZGBjZt4deA/wjmrbo4ATgfsAxwLvj4j+afJ8B/CeKq+NVd5ExJHAG4CHZeZ9gFd0fQC011u/dTsRsLrDHbv+vmDFkgG2GERLUm0zOf9LUi8M1xgZe6i/jx2TycTkno1rNg2P7awlbla3T3Sjtnra5tyNmugu+kRvqPprd+oTvWSwu6m4NDtdB9ERcVxEnAOMAr8FRiPinIh4Yo3NHwRcnplXVDXCnwGOb0lzPPCJ6vnngEdXJ+rjgc9k5vbMvBK4vMqvbZ7VNn9U5UGV5wnV85cA78vMjQCZeXOXh0H7gFu3lcEXphqhceXSAW4bsTm3JE1nlud/SZp3I+MTLBuauqHtUFVj266P88bhMdYsbxNE1+wT3Qhgp6sJXj7Uz2B/dNecu2phubpN+aD09QYYtV90T3QVREfEnwL/A2wFXg48o/q7FTizWj+VQ4Brm/6/rlrWNk1m7gA2U5pjd9q20/IDgU1VHq37ugdwj4j4QUT8qGoOrkVmw9bOE9I37L900JpoSZrGHJz/JWnelTmapw5vBvvL+uHte1aibNzWuTn3+ESyo0Nf6p37H69XEx0RrFo21FVNdKM5d6dr20bg7gjdvVFnYLFmfw18KDP/omX5ByPig8AbgQ/NScnm1wBwJPBI4FDguxFx38zc1JwoIk4BTgFYt25dr8uoWVq/bXvHQcUa9l86wPWbRqZMI0laNOd/SYvYyPgEy2vWRA+3GShs0/BY226AjWmzpquNHq0ZREOpUd48Ur9P9IbhMYYG+jr2+W70iR4dtya6F7ptzn0g8IUO6z4PHDDN9tcDhzX9f2i1rG2aiBgAVlEGGOu0bafl64HVVR6t+7oOODMzx6um4b+iBNW7ycwPZ+YxmXnM2rVrp3lp2tus3zbWcXqrhv2XDrBt+w4m00FnJWkKsz3/S9K8Gx6bmLYp9VB/+yB6bMck28Ym2jaXbgTF0wXRjT7R0w0sBqVfdFc10VU3xU7DUTT6RG/fYU10L3QbRH8LeESHdY8AvjvN9j8BjoyIIyJiiDJQ2Jktac4EXlA9fzrwzczMavmJEbGkGnX7SODHnfKstvlWlQdVnl+qnn+RUgtNRBxEad59xTRl1z5m/daxaWui91s6SALb2jTpkSTtNNvzvyTNu9HxeqNzA4yM737tt2mkMYVUuyC6quWdZpqrnaNzT9OkHEpNdHfNucc79ocu+2wMLLS3djMAACAASURBVGZNdC9M25y7ZfTsfwE+EhEHUgLRm4E7AE+ljI794qnyyswdEfFS4GzKdFQfy8yLI+KtwHmZeSbwUeBTEXE5sIESFFOlOwO4BNgB/GVmTlRl3CPPapd/BXwmIv4OuKDKmyrt4yLiEsp0Wa/NzPXTHQvtO8YnJtk8Mj59n+gl5SuwdfsO9l/a+YdJkm5v5vL8L0nzLTMZHttRa3Ru2LMmuhHQrl4+xJbR3QPsXTXRUweo28YmWDLQx0BfnSB6iEtuuG3adA0bt0091k9jYDFronujTp/oX1DmUm4I4E+rR1b/N3yVEsh2lJlnAWe1LHtz0/NRyoAl7bZ9G/C2OnlWy6+gjN7dujyBV1UPLUKNEQwP3G/65twAW0d3lI4DkqSGOT3/S9J8GpuYZDJ39V/upFOf6Ma145o2QfTSmn2ih7fvYMWSekNOrV422NXo3BuGx7j3nVZ2XD800EdgTXSv1HmXHzXvpZDm2PpGED1NTfR+1Q/dFptzS1Irz/+S9hl152jeVRPd2py7URM9yDUbdt+mbp/obWMTrKjRH7qxn+GxCbbvmGDJwPTbbNzWfvqthr4Ihgb6GLUmuiemDaIz8zu9KIg0l9ZvrRlEN9dES5J28vwvaV/SCHCn6xM92KEmetNw53mYl+3sbzx9TXTd7oGrqlHAN4+Mc4f9py7zxGSWboptRg5vtnSwn+3WRPdEt1Nc7RQRfcDS1uWZOTyrEkn/P3t3Hh7XfR72/vubfcFgBvtGAFxEUiJFSrSozZZtJd4Uy/HSxInj2nVb9zpNky7X6a2Tx62bpE1vnLZOffskadMkt9kcXceObdmWLXmRHMvWQi0UJS4gRRL7jtkw+/a7f8wcrLMCA2AAvJ/n8WMROHNwKJFz5j3vVgcL0SRAxcFidosZm9kku6KFEKJKcv8XQjQiIyiuVM5t9A7H15ZzF3qii+2JtphNWM1q3WvWiqaydHudVV2vz5kPtoOxNJ2edW+pq4TjaXIaWiokh+wWk/REb5OapnOrvE8Vhn6lgcUi/xNixy1nosv3REM+Gy3l3EIIUZrc/4UQja7acm5ricFigVgKm7nMHmaruXJPdCpTdTl3V3M+cJ4KJSoeOxmKA9DhKf+51mE1V8yWi/qodcXVvwB+jfyUa0V+yNdvkd+zPAx8op4XJ8RG+aMpzCaF11m5pMZjt0g5txBClCf3fyFEQzMC3EqZaLNJYTap9eXc0TRel7XkHmZnhQA1lsqQzmpcVQ4WG2h1ATDqr1zEc3Um/5zyeJen7HEOq4lkRsq5t0OtQfT/Afx74HcLv/6q1vo3gZPAFfK7m4XYcQvRJC0uGyZT8TfClZocFiKSiRZCiHLk/i+EaGhGJrpSTzTkh4vF1w0WKz+4y2k1ly3n9heG2labie702LFbTIxVEUQPTUewmhUH291lj7Nbas9EZ3I5clpXPlCsUmtP9CHgvNY6q5RKAz4ArXVOKfUHwB+Tf1ItRF184bnRkt/78L0DJb+3EEnRXqEf2uBxWLgxF6352oQQYh+R+78QoqEZmWVHhXJuyK+DWl/OncZXZnCX02YmVGYlVSCa/161K65MJkV/q4vRhWqC6DBHOpqWStFLsVtMNQ0W01rzp0/fpNlp5UN3l/5cLdarNRO9ADQV/nkUOLPiey1AdZ30QmyxhQoL6VdqsluIp7NkslL+IoQQJcj9XwjR0BJL07krB7FOq5m5SHLV14Kx8pnoSv3GxlDbajLhhoFWV5Xl3BGOd5cv5V66xhoGi12bjTC8EGNuMVn5YLFKrZnoHwF3A48BXwB+QynVCqSAXwa+V9/LE2Jj/NEUt/d5qzrWY8+/YUpJtxBClCT3fyFEQ4tVOVgMoNfn5LWJEFrrpR7oQCzNGWeZTHSFwWKBwoqsajPRkA+in7/pX3Uda4UTaSaCcT7cVTlTbLeaSGc12Vzl8mytNd+/MgtAVD4D16zWIPo3gL7CP/8n8uVc/5D8E+jvAP+8Xhcmdp+c1owH4nQ3O7BZai1yqK/5SLLijmjD0q5oeQMRQohSfgO5/wshGli1g8UADrQ4eWk0wEQwzoEWF1prQrE0PneZnmibmUQ6RzanMReZueM3yrmryIQb+ltdRJIZ/viHN0sG38e780VAt1aTibbkf+/VrLm6Phdl1B+j2WEhmsyWDeTFejUF0VrrIWCo8M9J4F8W/icELw4H+Mr5CSwmxeEON8e7PJzs89Jc5dL5ekllciwmMlUH0Z5CEL0oE7qFEKIouf8LIbbDRmfhAEuDwqrJRB9oyXegXBgPcaDFRSyVJZXNFd0RbTB6rSOJDN4iZd/+aBKTymeDqzVYmNDtj6ZKBtFD0xEAjlWYzJ2/xvzPTlTRF/3k0CzNDgv3HW7jiUszJNK5qh5AiLwNpwuVUgeUUncrpfoqHy32g3MjftqbbNx7qJWFSIqvX5ji97//+rbvqzOmI7ZWOVisyS6ZaCGEqJbc/4UQjSiezmIxqaqqIbu9DmxmE6+MBYHlUuxK07mBksPF/NE0LpsFUw3Z3IG2QhBd+PnFDE2HcdvMS4F/OfYqM9E356PcnI/y5qMdS+tgpaS7NjUH0UqpX1JKjQEjwHPAqFJqXCn1z+p+dWLXmA4lGA/EufdQGw+f7uVX33mcjz9wiMVkhqdfn9/Wa5kvDIpoc5dfSG8wguhKmeh4KsuVqTB6i9cATATi/JcnhviLZ4b54bU5xgOxqnpbhBBiK8n9XwjRyGKpbFVZaACLycRtvc28Mp4PooOxfGDsrdATDaWD6EA0VdNQMYD+FtfSa0sZmlnkWLenqlJrI1teKRP95JVZ3HYLdx9slWTSBtVUzq2U+gz5PZF/AvwtMAt0Aj8D/D9KqXat9W/V/SpFw3txxI9ZKe7s9y197UhHE7f3eXn62jz3HmrdtmsxMtFtVWaiLWYTTquZSLL02gKA528u8PilGd58tJ2HTnZvWd/I9bkI/mgKBVyeXgTygyf+6VuPbMnPE0KISuT+L4RodIl0tqZy5DsOePnyi+Nkc7qqTLTDls89hhOlMtGlS7JLcdrMdHjsLJQIorXWDE0v8q6T3VWdz17IwifLVIG+NBrg9bkID53sxmYxLV3zVgbRmynTb1S1Dhb7ZeA/aa3/3Zqvf1spNVP4vtxE95lMLsfLY0Fu6/Gse/N454kuLk2GeHJoll/cpiDQWDFQbU805IeLVcpET4UTAPzw2jwKeNcWBdIL0SQum5lffedxwok0T1yc4eXRAGlZwSWE2Dly/xdCNLRYqtYg2sefPzPCjbnIUia6pcxnx4rl3LEU7g30FA+0upYSQGtFkhkCsXRV661guR87kSn9mfG7l2YwKbj3cD7BZWSioynJRNei1nJuJ/B3Jb73A8CxucsRu9HlqUViqSxnD67PNrc32Tl7sJXnb/oZWYhuy/UsRAqZ6CrLuQE8dguRCkH0bDjJ8S4P9x5q5e+uzfPEpZktKe2ej6Rob8pfe7PDyrGuJjTIDj8hxE6S+78QoqHFayjnBrijP78K9fxYkGAhE+3bRE90IJrCVWMmGvLDxUqVc8+E85/9jlcxVAyWy7nL9UTPhJN4HNal/mmXvTAwTcq5a1Lrf+mvAn+P/DqLtX4G+Mamr0jsOi+O+PE6rdzS2VT0+z95aycvjwb4L09c5b//wpktv56FaAqLSdHsrP6Pd5PDwnggXvL72ZxmbjHJ8W4P7zjRhQZ+cHUOh8XE379vsA5XvWwhkuRIx/K/y67m/GfT2cVEXX+OEELUQO7/QuxRe6XUNl5jOffh9iaa7BYujIfo8OSTF74N9kTnCiXhG8lE97e6CMXTZHI5LKbV+c2ZQhXksSoz0caKq3I90bOLiaXNNJDvD3dazUST2zsIeLerGGUopd694pffAn5XKXWQ/A3V6In6AHAS+Df1v0TRyELxNNdmIjx4vKPkNMJmh5U33dLO11+Z5Bffcpjb+7xbek3+SIpWt62mUutKmej5SJKs1nQ12zEpxXvv6GV+McmLo4F6XPKSeCpLOJGhrWk5i97WZMOklp9GCiHEdpD7vxBip2WyOSzm6gpn46lsTYO9TCbFqT4vr4wHuWuwBbfNXHayt81iwqQgXCSIDsXT5DQ190RDvpxbA8FomnbP6irK6XCC9ibbUoViJVazwqTK90TPFjLRK7ntFpnOXaNq/kt/A9DAyoikD3hXkWP/EvjrOlyX2CVeGg2ggbsGyw8Oe8vRDs6PBfn9J1/nDz9yV80/ZzqUoNVtq2ptwUI0uSoIrYbHYSWVzRFNZoq+ARpPAo2ssEkperwOxgKxui6nHy6UvLevGIpmMZlob7IzG5ZMtBBiW8n9XwixY+YXk3z++9f4xJsP01/Yp1xOLJUtW45dzB39Pv7k6Rv0t7rwldkRDaCUwmE1F81EGyuqXLYNBNEr1lytDaJnwomq9kOvvEa7xUyiXDn3YmJdebjbbpZy7hpV81/60JZfhdiVtNa8OBLgcLub1gpDvBxWM++/s48vPDdKKJ5e2klXjVF/jP/5g+vc2e/jg2f7Kx4/F0nVNFQM8uXckM84lwqiTYpVTwK9LhvprCYYS5cdRFGL4fl8EL32IUBns4PJYOlycyGE2AJy/xdC7JjhhSjZnGY8EKsqiM5P564tiL3jgJd0VvPcjQW6vZVHOzhLBNFGT/NGB4sB64aL5bRmNpzk7bd11XQ+u9VEskQ5dzKTJRhLryrnhvxwMZm9U5uKf9K01iPbcSFi9wnE0vijKd58tL2q4z9wpo///eNhvvXqFB+6p7oem1Qmx5deHEMDFyZC/NSpnqUpgsVkc5qr04t86J7KwfZKxjnnFpMMtrnXfX8mnKTNbce6oqTIeBAwGYrXL4heiAHQvuZ8Xc12Lk6E8kMzNvAGLYQQtZL7vxCinK3upZ4oJA9KrX9aK78nuraZyXcUVrPOR1Lc2t1c8XinzUy4SPufcY3lyrlL/fvSWmMxqXVBdDCWJpXNcWuV/dAGh8Vccjr3bKE1sLlIOffN+e0ZALxX1DqdG6WURSn180qp/66U+qvC//+cUqr2+gWxqxklzj1eZ1XHnz7g5XC7m6+8PFH1z3j84jTzkRTvvaOXbE5zbthf9vjrcxHi6Synauy7Np7IlXoKNxNO0NW8OjvsKwTRU8H6lVkPz0dpsluwr5ku2eVxoIHXZyN1+1lCCFELuf8LIbaTUYFnbF2pJJ7O1lxO3eN1LFUZVlMKXikTXUtPtkEpRavbti6IrnWomMFuNZEo0RM9W/icu7YnusluIZ7KktuCrTN7VU1/0pRSncATwGlgGJgB7ie/H/IVpdQ7tdZz9b5I0ZiMv9ydnur6j5VSvP9MH5/7zlUmgnH6fMvBd7Gnc6/PRnjmxgL3H2njvsNtXJoK89yNBd5ytAOzqXgP8qvjISAfsNdiKRMdWR9Ex1NZ/NEUdw74Vn3dyERPhepXZn1zIUpb0/qsdmchgL86s8ipGn9vQmyFvTLNVVRH7v9CiO2UzWmmQvnPmdVmouOp7NKKp2oppbiz38t3L8/SUqEnGvLticUGi22mJxooH0TX0BMN+Uz0YrL4Gi5jvs7acm633YImn80X1ak1E/05oA24T2t9WGt9v9b6MHBv4eufq/cFisY1HU7gc1lresN6/519ADx6frLscYl0li+/NE57k413negG4P7DbYQTGS5PhUu+7tWJEC6bmUPtxddtleK2W1AUz0S/PhtBk88Gr9TksGBSMBmqbya62H7rNrcds0lxdXaxbj9LCCFqIPd/IcS2mYskyeQ0XqeVQDRVMUOayeZIZXM17Yk2nD6QT5K0VJmJLhpER1I4reWne5fT4rbhj6XQK36f0+EELS5r2TbGYsr1RBuZ6Gbn+kw0yK7oWtT6X/rdwKe01s+v/KLW+hzw68DD9bow0fhmw8l1gWUlA20u7hps4Ssvj696o1jrW69NE46n+eBd/UtvSMe7PbS4rDxzY6Hk616dCHGyt7lkproUk1I02S3MF8lEX5nOB+3dzY51r/E6rUzVaeBXNJlhdjG5ajK3wWxSdDTZuTYj5dxCiB0h938hxLaZDOQ/W53q85LVumgJ9UpGtrq1yGeoSoy+aG8VmWinLV/OvfYzrD+Wqjhkt5xWl41UJke0kAnO5jRj/tjSVphaOCzmkuXcM+EEFpNaV3ZuDESTNVfVqzWItgOlUmGLQH2mK4mGl81p5haTG/rL/f4zfVydiXB5qvgfpdlwgheG/dx/pG3VNEaTUtx7qI2b81Gmi2R/M9kcFydDnOrzrfteNZocxScTXp1ZxGJSRd+YvU5r3TLRxnqrUuu5OpvtXJ2RTLQQYkfI/V8IsW0mQnFsZtNSKXOlvmij9HltwqMabxjwcUe/j7sGWyoe67SayeT0urLnQHRzQbSxVcborf7x9XkCsTRnq7imtRxWE8kSg8Vmwkk6PHZMa1azuiUTXbNag+hngU8ppVaNLy78+lOF74t9YD6SJKv1umFb1XjPqR4sJsVXzxcfMPbEpRlsFhM/cbxz3ffODrZgMSmeLZKNvj4XJZHOcepA5emKxZQa7z80E6GzyBsO5IPoevVED8/nJ3OXWs/V6XEwHojLU0IhxE6Q+78QYttMBuOFoV/5z0QL0fLrl2YKU6c38rnU47DytV9+E3f2V07CGC2M4cTqzLg/mtrUphbjtf5oilA8zfcuz3Jrt4fbemr/TGsvBPrJIruiZxcTRWcZGeXc8hmzerUG0b8KnATGlFKPKKU+r5T6a2AMOFH4vtgHjCd+G8lEt7htPHi8k6+dnyCbW10OM+aPcWkqzJuPthddE+CyW7iz38fLYwFCsdVvYBfGgwAbzkR7SmWipxdL/j69ThvToQS53OanGS5noou/CRs3BpnQLYTYAXL/F0Jsi5zWTAUT9PqcNDut+fVPFTLR05vIRNfCWDO6trzcH0uVTIJUwxhqthBN8Y0Lk2g07zndiyqSwKnEXmiDjBRZxTUbTtJZ5N+R02ZGIUF0LWoKorXW54GjwB8BHcA7gE7gfwBHtdav1P0KRUOaCScxKeiocjL3Wh8408dMOMlfPbe8hlRrzbcvTuO2mXnTLaV3T997uI10VvPoK6sz2a9NhHDbzBxuX7/nuRpNditzkeSqPpdQLM10OFE6iHZZSWc18xWekFbj5nyUTo8du6X4UAyj/3yoAUu6v3Npmv/1wxs7fRlCiC0i938hxHaZjyRJZXP0+ZyYCuufKk3ong0nMKnSLXH1YgwuW5vICUTTVU33LsVmMeFxWHh5NMDFyTA/cbxzw+XhRra8WGn27OL6la2Qb5l02y1EkjKdu1pVj3tTSlmBe4CbWutf27pLErvBTDhBm9uO1byxKYTvONHFm25p4zNfu8j12Qi3dHq4MRfh5nyU95zuKRlIAvR6HXQ3O/jSSxN89P6DS1+/MBHiZJ8XU41DxQweh4V0Nj+8wld4IzQC1lJB9Mpd0Z01Dllba3g+ysEyDwBam2zYLCauNWAQfWV6kelQglSJHhwhxO4l938hRD2VW5EIMBnMZ5V7C6tQi61/Wms6lKDDY695sGytHNb8597wiixvMpMlkszQ6q483bucVpeNEX+MjiY7DxwtnUyqeI2FTPTimkx0MpMlEEuX/LzaZLdIJroGtURAWeD7wK1bdC1iF5kJF3+SVS2bxcSf/aN7+PgDh/izZ0b4k6dv8O2L07S4rNxzsLXsa5VSnBnw8cpYcKm0OZPNcWkyzKm+je9QbirszFs5oXs5iC7+e63nrujhhSiH2koH0SalONLRxNUGm9CdzuaYCSfQLJf5CyH2FLn/CyG2zWQwjsWklqod29w2FqLJsltdZhaTW17KDSsy0SvKuQPR/D+3FllRWgsj8/zeO3uxmDaWpIJ8TzSsD6KNlsVSn2lddrMMFqtB1f+FtNY54BrQvXWXI3aDdDaHP5raUD/0ShaziX/3nhP8t5+/k/FAnKlQgrff1oWliuz2nf0+zCbF3740DsC12QjJTI7TBzYeRHsKPdizK/qir04v4rFbloLltYyvG09NN2oxkWY+kiqbiQY41tXUcJno6VACoyW82NR0IcTuJvd/IcR2mgzG6fY6lrLKbU120lm96vPZWjOhRNFe33or1hNtZMk3m4l+4Gg7f+9MH0c6mjZ1HofFCKJXl5wbw9ckE10ftT7m+DTwGaXUqa24GLE7zC4m0WxsqFgx7z/Txz996xEeOtm9tKuvEo/DyluOtvOVl/PDyV6dCAFw+2Yy0YUgeuVwsaGZRY51e0oOdnDZzNgtpk1nokcW8pO5D7W7yh53rMvDZCix7o1xJ40X9mSbFEyF6zOpXAjRcOT+L4TYclprJkNx+gql3LC8tWR4PlrydTOLiW3JRC9N516ZiY7lg+jN9EQD9HidnK1QjVkNe6HkfG1WebZQLdhZIhPttluIpiSIrlatQfS/BdqA80qpUaXUOaXU8yv/twXXKBrMZiZzl9Lrc/KWYx1F10iV8jN3HWAqlOCZ6wu8Oh6iyW4pWw5diceRf4JoBNFaa67OLHK821PyNUopen3OTe+Kvlm4MVTKRB/tzD+dvNZAE7onA3HcdgsHWlySiRZi79r0/V8p9ZBSakgp9bpSqmRvtVLqZ5RSWil1tp6/ASFE4/NHUyTSuaV+aFgeFmYkHNZKpLMEY+lNtRlWyxh0NupfvhZj6Fmp7SrbrdRgMSOTXy4TnUjniq7GEutVPVis4LXC/8Q+NhNOYDGpTS2Vr4e339ZFs8PCl18a5+Z8lJO9zRseKgb5YRE2s4knLs0w6o8xHogTjKU53lU6iAbo8TqYCm4uA2s8XR1sdfPSSLDkcccK13JtZpE3DLRs6mfWy0QwzgGfE5/LyivjQbTWG1rJIIRoaJu6/yulzMDvk5/qPQ6cU0o9qrW+tOY4D/Avgec2ca1CiBrltCab0xseGFsvRlJiZRDtdVoxqeVVoGvNLu2I3vpMNMCDxzv4zqUZUpkcNouJQLQ+meh6sZcYLDYTTmA2qZKruJps+bDQH03R43UWPUYsqyqIVko5gXeTv4FOA9/VWs9s5YWJxjUT3p4JiJU4rGbec0cvX3lpgqzWfOz+wU2dTynF0a4mnr/pZ2h6kV6fk3ed7OIdJ7p4amiu5Ot6vE5+fH1+Uz/75kKUHq9jqdemlP5WFw6rqWGGi6Uy+aFiJ3qb8TgsPHczx3ggTn9r+bJ0IcTuUMf7/z3A61rrG4XzPgK8D7i05rj/AHwW+L82fNFCiJq9OBLg8YvT/NpP3bqpoVabNRmMY1ZqVVbZbFK0FCZXFzOzWP8KyXJ++nQvf/vSBD+8NsfbbuvCH02hFEubXXaa1WzCbFKE17T+zS4m6fTYSyac3IW2xoWIBNHVqBhEK6UOA98FDq74clgp9XNa6ye26sJE45oJJzm0wV3M9fYzb+hbWpWwmX5ow5d/6Y1kcnqpP7oavT4HM+EEmWyuqqFoxQzPRzlYRSm62aQ43N60NJV8p02F4migz+fEXXgAcHkqLEG0EHtAne//fcDYil+PA/eu+XlvAPq11t9USkkQLcQ2GvXHiKWyLCYyO5pRnQjG6fLa1wXybU02Rkpkoo1Wsu0Kot90Sztep5VvXphaCqJ9TuuOJ5dWanPbGJpePYh2Jpyg01O65N1tz3+OW7mlRpRWzSf+3wVywJsBF3ASeBn4n1t4XaJBhRNpQvH0tr1RVfKGgZalgP70geqGkpXjsJprCqAhn4nO6fx6hY0aXohxsMJQMcPhDjc35hsjiJ4olLH3+Zx0eR0o8jujhRB7wrbd/5VSJuBzwK9WcewnlFIvKKVemJsrXSUkhKieETgtxmsfXJpIZ5nfxGcgg9aayWCc3iJZ0Fa3nZH5WNE1V8asnu0YLAb5Na3vOtnFE5dmSKSz+GMpWna4xXGtwTY3Lw4HyOaW/33NLSbLTjA3Pv9W2skt8qoJou8H/q3W+kda64TW+jLwi8CAUqpnay9PNJprFfYmbzelFP/4gUPc2u1hcIeynz2+/BvSRvuiQ/E0/miqqkw0wJGOJsYDcRLpnR/8MBGI43FYaHZasVvMtLptXJ4K7/RlCSHqo573/wmgf8WvDxS+ZvAAtwNPKaWGgfuAR4sNF9Na/5HW+qzW+mxHR0eNlyGEKMYIgsOJ2qczf+fSDP/j766X3eNcjWAsTSyVpa9lfRDd5raxmMwUDfBmwgnsFhPNzlpHPW3cw6d7iSQz/N3VOQLRFK0NUsptONjmYjGZ4cr08meyypno5XJuUVk1f9p6gBtrvnYdUOR3Rk7V+6JE4xqazmdAGyUTDfDR+wb56H2b64feDOOJ6UYndI8VenwG2yo/BPjCc6NMhxJoDX/w5HW6vcv/HT5878CGfv5mjAdXr6Ho9jokiBZi76jn/f8ccFQpdYh88Pwh4MPGN7XWIaDd+LVS6ingX2utX9jQlQshqhZPZYmm8g/mFzewJ9goBY+lskuB2EaMr6huW8uYfD28EFua1m2YCSfp9jq2dajpG4+00eKy8o0LU/ijKQYarI3N2PZy7qafk71ekpksgVj5SlK7xYTFpJiPSjl3Napt4NzcoyWxZ1ydWcRmMeFzbm6h/F6y2Uy0EURX20fcUXiKOLfDPSvJQvnWyifG3V4HI/4Y0Q3chIUQDaku93+tdQb4FeBx4DLwRa31RaXUbyml3luPnyGE2JiVPbC1lnNnsrmlnmRjX/JGGUPFipVlGxthivVFz4QTdJVY27RVrGYTD93ezXcvzzAdTuz4xpq1Wlw2er0Ozg0HgOX1reUy0Uop3HbLlmWi5yNJJje5zaaRVPu46HGlVLFPxd9b+3WtdefmL0s0qivTYbo8dllhtEKzw0qT3cLUBjPRozUG0e2FJ7Bzdeg/2ozJUAINHFjxxLin2YnWMNRAK7iEEJtSt/u/1vox4LE1X/tMiWMfrPE6hRAbZATRivVrkSqZDifIFsq4A7E0BzZx658Iq1N5QgAAIABJREFUxOn2OooOaW112VCq+K7omXCCU3WYi1Orh0/18tfPjxFLZRuuJxrg7kOt/Pj6AlprZqpcA9Zkt7CwRUmax16dYiGa4v98+7EtOf92qyaI/s0tvwqxK+RymouTYU70NO/0pTScHq9jw0/XRv0xfC4rzY7qsvs2iwmv07rj0xONoWIrdzn2FMrLL0+FJYgWYveT+78Q+8B8JIlJQafHwWKytkz0eGD5s09wE5lorTXjwRin+4oHwxaziV6vc10m2ggQ314mw7pV7jvcSpvbxkI0VXL38k66+2ArXzs/ychCjLnCGrDOCjON3HYzC1s0WMwfTRGIptBa74lkXMUgWmtd15uoUuoh4POAGfhjrfXvrPm+Hfhz4C5gAfh5rfVw4Xu/DnwcyAL/Qmv9eLlzFnqvHgHagBeBj2qtUyt+1s8AXwLulr6rykb8MRYTmaK9Kvtdr8+54Uz0WCBecy9NR5N954PoQAyv04pnRfDvc1nxOCzSFy3EHlDv+78QojHNR1K0uGz4XFaCsdqC6IlAHLfNTFbrTZVz+6MpEulc2c+YB9tdDK/JRIcTGeLp7I7M6rEUSrr/6rnRHV0LVso9h1oBeH7YT7zQ895ZoezdbbMwuwWVjlprgvE0mZwmksys+uy4W23rNnWllBn4feCngBPALyilTqw57ONAQGt9C/B7wGcLrz1BfhDJSeAh4A+UUuYK5/ws8HuFcwUK5zauxQP8S+C5rfi97kUXxoMARacm7ne9PgdToY33RNe6V7ndY2duMbnpSZibMbFmqBjk+2lu627m8pSsuRJCCCF2g/lIkvYmOx6HlcVEjUF0ME5fi5MWl41AtPb1WCvPA+U/Yw62uddlomcL6626vDsz8Pb9Z/qA6lvyttMtHU34XFbO3fQzu5jAbFIVM+ZNdgsL0fp/vkykc6QyOYCaH9Q0qm0NooF7gNe11jcKGeFHgPetOeZ9wJ8V/vlLwNtUPuf/PuARrXVSa30TeL1wvqLnLLzmJwvnoHDO96/4Of+BfJC9sfThPvTqeAi7xVTxKdZ+1ON1Mh9JkczUtnYqm9OMB2L0t9SaibaRzOQ2NEWzHhLpLPORVNGb3a09HoamF8nlZB6hEEII0chyOV0Iom00OyxEU9lVu4XLSWVyzIQTHGhx4XPZNpWJngjGsZhU2XLjIx1NBGLppUFmkO/JBujagXJuyJdM//Df/AR3H2y8FjaTSXF2sJVzw35mwkk6muyYTOXLqN12C4l0jliqvmtUg/HlPxubHUDXKLY7iO4Dxlb8erzwtaLHFKZ5hsiXY5d6bamvtwHBwjlW/Syl1BuAfq31N8tdrFLqE0qpF5RSL8zNzVX7e9yzLkyEONHbjLnCX8D9yOgFnq6xpHs6nCCd1bWXcxceZOzUcLGJMmsobutpJpLMrOqTEkIIIUTjMT6HtHvsSyW21Wajp0JxNPnPAi2FUvCNZjCXhoqZSocm9xbKk5+5Mb/0NWNgVvcOZaIhn4Vu1B7few61MLwQ47WJEF0V+qEhn4mG+u+KDq3IPksmepdSSpmAzwG/WulYrfUfaa3Paq3PdnR0bP3FNbBsTnNxIsTpPu9OX0pDMoZrTQZrC6KN9Va1BtHthX2JO9UXbQTvxXqQbisMnrskfdFCCCFEQ7s5ny+Pbm+y0+zIB1DVTug2HpYb5dyp7MYymDmti7aIrXVbTzPNDgvPXF9Y+tqMkYnegZ7o3eDug/kHD1emF5cSMOUYe77rvSs6WFidZlKrs9K72XYH0RNA/4pfHyh8regxSikL4CU/YKzUa0t9fQHwFc6x8use4HbgKaXUMHAf8KhS6uwmf2972s35CNFUdkdWCOwGRia61r7o0Q0G0c1OK1azYn6HMtHheBqTAo9j/WzC410elEKGiwkhhBAN7saKIHo5E11dED0RjNPssNDssNLiyr92I6W6/kiKZKb8UDEAs0lx3+E2nrmxOoj2Oq04rOaaf+5+cHufF2fh3001mWi3PX+sv86Z6GAsjVkpOj2OTfXON5Jq90TXyzngaGFq9gT5QWEfXnPMo8DHgGeAnwW+r7XWSqlHgS8opT4H9AJHgefJr7Vbd87Ca54snOORwjm/prUOAe3GD1NKPQX8a5nOXd6F8RAApw94eaGwuH2nfeG50ZLf+/C9A9t4JfmeaKDmCd1j/hgmBT2+2p6gmpSio8nO3A5lokPxNB6HFVOR8iWnzcyBFufS020hhBBCNKYbcxGsZkWzw4JxRw9XWc49HojTV5jp4itMp97IrujxKoaKGe4/0sYTl2YYD8Q40OJiJpyoKjjcr6xmE2cGfPz4+kJV2fqlcu66Z6JTeF1WWtw2/HU+907Z1kx0oT/5V4DHgcvAF7XWF5VSv6WUem/hsD8B2pRSrwOfBH6t8NqLwBeBS8C3gV/WWmdLnbNwrk8Bnyycq61wbrEBF8ZDOK1mjnQ07fSlNCSnzUx7k22pPLtaY/4YvT4nVnPtfxWNCd07IZRI43WWXk/Q43VueFq5EEIIIbbHzfko7U12lFK47flAuppMdDiRZj6S5EAh8DVWPG1kV/SkMVSsinLj+4+0ASyVdE+Hk1LKXYFR0t1ZxfC1JrsFk6Luc21CsfznRt8me+cbyXZnotFaPwY8tuZrn1nxzwnggyVe+9vAb1dzzsLXb5Cf3l3ueh6s5rr3u1cnQtzeJ0PFyhlodTG8UFv2ddQfq7mU29DRZOfV8RDpbG5DQfhmhONpur2lnxj3eh2ca5CKBSGEEEIUZwTRkC+XbrJbqhos9tpEvkLRKMF22sw4rKYNlXOPB+L0+pxVfcY81umh1W3jmesLfPBsP7PhBEc72yu+bj970y3tfP5716r6vGkxmzje3cz5sWBdryEYT3O43U2LK79dJp7O4rJtexhaV/tusJioXSab4+JkiFN90g9dzsE2N6MLtWWiR/3xmtdbGdo9djT1n6BYidaaUDyNt0g/tKHX52QmnKh6TYYQQgghtlcyk2XMH1sKoiE/66SaTLTR5reyj3kju6JzWjMZqjxUDPJtfI+cG6PX6+B7V2b5y2dHmAkndmw+zG5xz6FWvv4rDyxl8Su5s9/H+bFg3VaVZrI5wvE0PpcVX6GKcS9M6JYgWlR0fS5KIp3j9AGZzF3OQJuLqXCCRLq6yZSxVIb5SJKBto1nooFt74sOxzOksxpvoXSrmB6fk0xh96QQQgghGs+YP0ZOL2/8APA4rFVlol8dD9Hisi5NcwY2tCt6fjFJqoqhYisd7mgiFE8zupC//uYy7WUi79QBb9VruM4M+FhMZJaGzm3WzGISDfictk2V/Tea3Z1HF9viwni+pOOUBNFlDba50BrGAzFu6fRUPN7oN+nfYDm38eR4s33RpQa0lRrONhXOX3e5nujewrTyyWBcepWEEEKIBnR9Lh8kdXhWZ6IngpX7YS9MBJeGihlaXFauz0Zq6nedqGGomOFwhxuA84XPp81lKuNE7c705ytPXx4NcEvn5mchTRb+G3tdK6e47/5MtPyp2+eqCaBenQjRZLdwqM29XZe1Kw0W/v2MLFQXRBul3xvtibZZTPic1m3P9hoTyMuVc6+cVn5mW65KCCGEELUwtmi0uVcG0VaiyQzZnC7Zo+yPphjzxzl5cnVyZSO7okcWYljNalUgX0lHkx2P3cKrhZJyYzWXqI8jHU147BbOjwX54Nn+Vd/7w6euMxGIcbDdva6nuVTyxQiifU4rTpsZm9kkmWixP1wYzw8VM8lQsbIGC8HwSJV90caO6P4anr6utRMTuqcLQXS58qle33ImuhHVmn0XQggh9pqbc1Ham2w4bcs7lpudFjQQTWZK3ucvTuaD1941JdgtS2uuqguQrkyFOTfs585+X9GVmaUopTjU4V7qy5Zy7voymRR39Pt4eXT9cLFvXJjk4mQYRb6S8lhXE3cNtpatTpxYkYlWSuFzWfdEJlp6okVZ6WyOS1NhTh+QoWKVtLpteOwWRqqc0D0WiOG2mWl1l+4trqSjyc58JLmtqwKmQgkU5Z/8ep1WnFZzzXuzhRBCCLE9bsxHONy+ulzXY8/f28vtijba0Vb2UgO0uKsv1Z0KxXnkhTF6fA7ed2dfTdcNcKRw3Yrl3caifs4M+BiaWSSWWh4yF01mGJpe5GRvMw8e7ySnNd+7PMu3Xpsqe67JYByn1Yzdkn9Yk19ztfsz0RJEi7KuziySyuQ41Sf90JUopRhoczFS5a7oMX+M/lZX1YMeimn32ElmclVN0qyXqWAcj8NSdhWFUooen0N2RQshhBAN6uZ8lEPtq1v1PIVWrXKfKyaDcUxq/cN0n7O6oVGLiTR//swIDouJf3DfQWyW2sMRoy+6qcLnEbExd/b7yOb0Usk8wPeuzJLJad54pJ13nOjinz14C7d2e5YqFEuZDCbwuZb/rLS4bHsiEy2PbkRZxl8emcxdncE2F5enFqs69sJ4iLYme8nS4mrsxITu6XCiqtKpXq+TyeDWZqLL/buT0mwhhBCiuFA8zXwkxaGO1UG0cX8vH0Qn6PQ41gWv1eyKTqSz/MWzI8RSGT7xliMbLsVuddvwOq2Shd4idxaGi50fC3Lv4fxqrG9emMTjsDC4YqtMZ7ODoZnFsitNJ4PxpdVWkJ/iHk9nSWayS9np3Ugy0aKsb1+cpqvZvuHhV/vNYJub8UCs4n5krTWBWIpW1+b6eDoLgzhmt7EveiqUKNv7YujxOhq2J1oIIYTYz8YKVXMH1wyNbbJbUJQv554KxenxFd+8UWlX9JdfGmc8EOeDd/XXtNZqLaUU7z7Vw1uPdWz4HKK0tqb8Z3+jLzqazPDU0Bwne72r+tc7PXZymrJDbieC8VVrUY2s9G7fFS1BtChpzB/jB1fn+Pm7BzZVcryfDLa6SGd1xeBxPpIindWb6oeGfNmV02pmZht7j6dD1WWie3xO5iL5/Y9CCCGEaBxG0NPhWf05xGxSuOyWspnoqVCCXm/xALilwq7oF0cCuO0WTvY2b+CqVzvV5+V2aTfcMmcGfJwfywfR37syS7JIe6exxrRUMiecSLOYyKzKRNc6gK5RSRAtSvqr50YxKcUv3NNf+WABwEBbdRO6jcncmw2ilVJ0NTuYDm9PEL2YSBNJZvBWsU6iz+dAa5jZpmsTQgghRHWMAKbVvX61VLPDwmKJTLTW+URBj7dUJtpKMJYuOfD0/FiQ/hanJGd2gTv7fUyHE0yF4jx2YYpOj31VKTdAe5MdBcyW+Kw3VWjrW9kTvVcy0dJIIIpKZrJ88YUx3nZr59LOX1GZURY14o/yAO0ljzPKqFpcmwuiAbq9dl4eDaK13vKbkjE8orpy7uVd0f3SDiCEEEI0jIVIIYgu8jnE4yidiQ7E0iQzuXXrrQy+wq7oQCy9LlEQiqe5MRfl7bd1bfLq62MzM2n2A6Mv+kevL/Dk0Cwfurt/3Soym8VEi9vGTIlM9Mod0YYme34Y3G6f0C2ZaFHUt1+bxh9N8ZH7Bnf6UnaV7mYHNouJ0QqZ6KUgepOZaMiX0iQzOSa3oaR7qood0QZjV7RM6BZCCCEaSyCWwmxSS9O4V/I4rCUz0UZQ1FumJxpgPLD+c9CF8XxpcH+rJGd2gxO9zdjMJv7796+RzOR496meosd1euwlM9HLO6KXP++alMLn3P27oiUTLYr6y2dHGGxz8cAtpbOpYj2TSdHf4mS4wq7oUX+MZocFq3nzz7G6C/0oQ9PhTQ3pqIaRifbVkIne6gndQgghhKiNP5qmxWXFVGQ9lJGJzhUpyTaC6B6vE3+RAWLGrujxQJzTB3yrvvdKob/2gE+q0xrZygx9V7OdkYUYHruFa7ORdZno/DEOrs4sks7m1n2unQzGsRR5WNPiskkmWuw906EE54YD/P17B4q+uYryDra5K/ZEj/hjdSnlhuWhDkPTkbqcrxwjE+1xVn7+5rZbaHZYJBMthBBCNJhANFVyLovHYUWTn8i8lvE5oNR0bmNXdLFM9PmxIIc73Dhtu3et0X5jtOOd7GsuGkDD8oTu4fn1CaTJYJxur2Pda32F3vndTIJosc5zNxewWUx88C4ZKLYRA20uRv2xkkM10tkcFydCdJcYylErh9WM12llaDpcl/OVMx2O095kx2Kq7q2j17f1u6KFEEIIURt/NFXyYX5zIWtYrC96MhTHala0FxlIBsu7oscDqx+ga605PxZc6rMVu4Mx6+d0X+n/bp2FZM7VmfXJnMlgomj/vM9lZTGZIZ3dvRtcJIgWqyTTWc6PBXnPqZ669OvuRwfb3MRSWeZK7My7MB4imspyuKOpbj+zu9nBlenFup2vlKlQouREzmJ6vA7JRAshhBANxh8rn4mG4ruip4KJfGaxTKVil8fBczf8q5IJE8E485EUZySI3lVO9Dbzyz9xCwfb3SWP6ShM6L42u/5z6EQwXrTV0HiAE9rF2WjpiRarPDk0RzKT42NvPLjTl7Ij6jGp0VhzNboQo9OzPuB89sYCAIfLvCHVqqvZwTM35ov2o9TTdI2Ttnt8Tl4ZD23Z9QghhBCidoFoqmSyxFMmEz0VipfcEW24c8DH185PcmE8xB2FoNnYN3xHv4/XJra+ck7Uh0mpivN2jAnd19ZkorM5zXQ4UXQInc/YFR3fvX3RkokWS6ZDCZ5+fY67BluW3vRE7QZby++K/vH1eW7t9uC21+8ZVleznXRWF+1HqadyuyGL6fU68EdTJNLZLbwqIYQQQlQrl9MEYinaSgXRdiOIXp8lLFWeu9IdB3w4rCa++MLY0tdeGQtis5i4tbt5E1cuGlWnx87VmdWZ6NnFBNmcLlnODbt7V7QE0QKAnNZ85eVxHFYzP3Wye6cvZ1c70OLCpGCkyITuZCbLC8MB7j/SVtefafRXb2VJdzSZIZzI1NTLvTyhW0q6hRBCiEYQiqfJaUr2RFvMJlw2M+E1mehsTjMTrtzW5bCaefftPTx6fpJ4Kv8Q/fxYkJO9zdgsEnrsRV3NDm7OR1f1OC+vQ1sfRDc7rJhUftXabiV/kgUA54b9jAXiPHyqB1cdM6T7kc1iotfnZMS/PhP98miQZCbHG4/Ud3VYR5Mds0kxtIVB9HRhB2BNPdFLu6JluJgQQgjRCPyFwKVUTzQsr7laaW4xSSan6alineYHz/azmMzw7YtTpLM5Xp0IyVCxPazTYyeTW10RaQyXK1YObjYpXDZL0Qnwu4VES4JwIs3jF6c50uGWN7g6GWxzMVyknPuZ6wuYFNxzqJVvXpiq28+zmE0canczNLOFQXQhEO5udnKzyrJx441TMtG1Kdeb/+F7B7bxSoQQQuw1gWg+iC43QLbFZWN+cfWA1MnCoNDeKh6m33e4lcE2F//fuTGOdXlIpHPyGXMPWzmh+2iXB601X3hulDa3jYFWFy8MB9a9xmUzE0vt3nY/yUQLvnlhikxW8747+1AldsCJ2gy2uRktUs79zPUFbu/z4nVa6/4zj3d7tjQTvbQbsoZMtFH6LZloIYQQojEsFILoUj3RAAOtLuYiyaWAG/KTuWG5VascpRQfvOsAz97w8+grkwASRO9hHU12lFqe0P3dy7M8d9PPv3rHMRzW4nvBXTaLBNFi95oKxXl1IsRbjnXQ3lR855+o3WCri0AsTSi+PDAhnsry8liA+w/Xtx/acLzLw6g/tmWlMdOFJ9C19ETbLWbam2yy5koIIYRoENVkogcL+4FfHFnOIBr38krTmg0/e1c/JgV/+vRNWgsZSbE32Swm+ltcXJuJkM7m+L8fu8yRDje/cHd/ydfkM9FSzi12qaevzWMzm3jjmkFX9Vj1tJ8ZN5+LEyHeeEu+//mFET/prK77UDHD8W4PANdmI1vytHcqlKDFZS35RLGUHq+TyeD2Z6IvT4X5nW9d4cHjHbz3jl7a5CGREEIIsdwTXWKwGMCBFidmpXhhJMDbT3QB+cncLpuZZmd14UO318Fbj3Xw5NAcdxzwSrXjHnesq4mrM4t84blRbsxH+ZOPncVSZu2qy2ZmzC+ZaLELTYXivDIe5K6DLbhs8jylnu473Ep3s4N/8+ULS098n7m+gMWkuPtg65b8zONd+SB6aHpr9i9OhxJVlXCt1eN17Egm+rPfvsLTr8/zm1+/xL3/6Xv8kz87x4sj/m2/DiGEEKKRBKIpHFYTTlvph+JWs4len2PVfXMqlF9zWUsw/HNn85lIWZ269x3t8nBzPsrnv3eN+w+38ZO3dpY93ijn1lpv0xXWlwTR+9j//tEwWsMDdZ4ULfJL5P/HR+9iNpzkV/76JTLZHM/cWOD0AW9d90OvNNDqwmk1b9maq6lQ5bUWxfT6nEt9VNtlIhDnqaE5PvmOYzz+r97Cxx84xPmxIP/kz14gm9udb9ZCCCFEPSxEU7S5K1dnDba5eWU8RDKTzxZOhirviF7r7Se6+KUHj/Czdx3Y0LWK3eNoZxOZwg7yTz98W8WHLS6bmazWRHdpX7QE0fvUYiLNF54b5fY+b9meGLFxd/b7+I8fuJ0fvb7AZx69yIXxUN1XW61kMqmlUpqtMB1O1NQPbejxOlhMZlhMpCsfXCdPDs3S7LDwD+4f5Hi3h19/9238+58+SSCW5vxYcNuuQwghhGg0gWiKFnflAaeDbS5SmRyvTYSA/KaNWh+mW80mPvXQrRxokX7ove5YoSLyA2f6uL3PW/F4tz1fCbFyeN1uIkH0PvXI82MsJjO8+ahkobfSz53t5x++8SBfeG6UbG7r+qENx7q2ZkJ3Ip3FH01tKBNt7JPcrgnd06EEl6bC/MM3HcLjWP6Q8Oaj7ZgU/GBodluuQwghhGhE/lialjL90AZjENgLwwFSmRzzkWTNmWixf5zsbeY/vv92/t3DJ6o63mglDcQkiBa7RDqb409/dJP7DrfKk8Ft8OmHb+PeQ624bGbuGmzZ0p91oreZ+UiK0SI7qtd6bSLEO3/vB9yYj1Q81sjeHi08ZayFsU9yYpt2RT91dRabxcQ/ftPBVV/3uWycGWjhqatz23IdQgghRCPyR5Nl11sZPA4rB9tcvDASYCacQGvo3cBsFLE/KKX4yH2DVVe4ugo9+YHY9lUq1pME0fvQNy5MMhVK8Im3HN7pS9kXrGYT//sf3cM3/vkDNU+2rtXbb8tP0PzWa1MVj/3st69wdSbCXz07ynwkWfbYJ4dmsZoVb7ql9sqFg+35SeXXZysH65s1t5jk1fEQ9x1qw1fkKfuDxzq4MB4iskVrwPajF0cCPP36PFOhOLldOhxECCH2k0A0XXWgc9dgKy+OBJYehPf4aq9IE6IYY7BdcJdmomUk8z70F8+McKTDzYPHOnnk3NhOX86+4LSZOdzRtOU/p7/VxekDXh57dYpffOuRksc9f9PPD6/N87H7B/mbF8f582eG+aW33lJyUudTV+a451ArTRsYitbeZKe9ybYlZeZr/eDqHBaz4oESbQoPHu/kv37nKtdmFjkzsLVVAftBTmu+en5iaViby2bmSEcTD93eTavMWhBCiIaTzGSJJDNl11utdPfBFr780jg/vr4AsKEtHXuNrIGtj6Vy7l3aEy1B9D4zshDlpdEgn3roVkwm2de3F737VA+/860rjPlj9LeuL9fXWvNfnhiiw2Pn137qNmwWM3/69E3+6vkR/tEbD2Fe8+diIhhnaGaRD569bcPXdLzbs2UDzwzRZIbzYwHuPdxWMtg/2dtMe5OdIQmi6yIYS5PNad55oguv08rQzCIXxkP84OosHzgjk1iFEKLRBAuls9Vmos8ezN8rv/7KJAC9konedns1aHdazSh2bzm3BNH7zNfO598E33tn7w5fydbazjeccj/rw/cObNt1GB4uBNGlstE/en2B52/6+Y2fPoHTZuZQu5sPnOnjSy+N8/ULk7z/zr5Vxz9VGMT14PHy+/7KOd7VzF8/P0oup7fs4c2YP0ZOw+29pSdCmkyKtx7r4LFXp8hpjamGXZdivYVovg1gsM3NoXY3t/d5eXU8xOjC9u8FF0IIUdlCJJ/1q6YnGuBwexM+l5Wb81G8TutS9lCIzTKbFA6redcOFpO/CfuILpRe3nOolT6Zrrhn9be6ONVXvKRba81//c4QvV4Hv7AiwH/DYAvT4QRPvz7PPQdbV03ffPLKHP2tTo50uDd8Tbd2e4ins4z6Y0s90vU2FohhUlT8s/3g8Q6+/NI44/4YA21bcy37xdoPY1aziWanlVF/5cF2Qgghtp8RsFSbiTaZFHcNtPC9K7MNPZl7r2Zr9zqXzbxrM9EyWGwfeW0izI256LpMo9h7Hj7dwyvjIcbWBDNPDs3y8miQf/62o9gtq/uff/LWThxW01LmGfK9Uz96fZ6fON6J2kTW9lh3fqr3lS3six7zx+lqdmCzlH9be/PRdhQwNLP1g872uoVIEpvZhMex/Dy2xWVj1B/dwasSQghRir/Qf1rL3IqzB1uB5W0bQtSLy2betYPFJIjeR756fgKrWfHuU907fSliiz18qgdYPaU7nsrynx+/ykCri5+9a32/qsNq5r7DbVycDDMbzu90fv6mn3g6y09sopQb4FhXE0qxZcPFclozFijeA76Wz2Wjv9W15T3a+8FCNEVbk23VA5Y2t42RKlasCSGE2H5LmegqB4vBcl+0TOYW9eayWXZtObcE0ftENqf5+iuTPHi8s+jqH7G3GCXd33x1GoBIMsPH/t/nGZoO8+mHb8NqLv5X/01H2rGYFT8o7FJ+8socdouJ+w63bep6XDYLA1sYuM4tJklmcvRXuff8WJeHiWBcVl1t0nwktS6b0eK2MbuYJJ7K7tBVCSGEKMVow2lxWat+zak+Lx0eO6f6Ss8cEWIjXDYzgejuLOeWnuh94pnrC8wuJqWUex9596kePvvtK1ycDPHpr7zGqxMh/tuHzvCuk6UrEdx2C/ceauPH1+cZXYjx1NAs9x9pK7n6qhbHuzxcmQ5v+jzFjAfymc/+lur6tY5VlFm0AAAgAElEQVR3efju5RlZdbUJOa0JRFOc7G1e9XWjP3osEONYl2cnLk00KKXUQ8DnATPwx1rr31nz/U8C/wTIAHPAP9Zaj2z7hQqxhwViKbxOK5YSD9OLcVjNPPvrb1u3vUM0tt3QJ57viZZMtGhgXz0/QZPdwttu21xZrtg9jJLun/3DZ7g4GeIP/v4beO8dlaeyP3BLO0opPv3VV7kxH910Kbfh1m4PwwsxEun6ZyhH/XEcVhPtHntVx/f4HLhsZm7MSe/uRgVjabJar5vwamSmR6WkW6yglDIDvw/8FHAC+AWl1Ik1h70MnNVanwa+BPzu9l6lEHufP7q+gqgaEkCLreCyW4ilsiQzu696TTLR+0AineXbr03zrpPdOKybzyiK3WGgzcXpA16Gphf5X//gbNUrqpqdVu4abOGH1+YBag6iSz35nIukyOY0r89GuL3OJWHjgRgHWlxVr6wyKUWP18HMYqKu17GfLETy663amlY/uDA+nI3IhG6x2j3A61rrGwBKqUeA9wGXjAO01k+uOP5Z4CPbeoVC7AP+aKqmUm4htpKrUOkYjKXpat5dMYoE0fvA96/MEklmeP+Znd0NvRvKSvaaP/zIXSTTWQ53NNX0urce7eDFkQCDbS4G2qrrM66kq5AlHpperGsQncrkmA4lat5j3dXs4NywX/ZFb9BCYcJrW9PqjIbLZsZjt6ybDC/2vT5gbMWvx4F7yxz/ceBbxb6hlPoE8AmAgYGBYocIIUrwR1McqHJ+iBBbzdg77o+m6GreXYPrtj2IrqInyg78OXAXsAD8vNZ6uPC9Xyd/Y80C/0Jr/Xi5cyqlDgGPAG3Ai8BHtdap/dZ39fVXJmlvsvPGI+07fSlim210H3iL28ZvvPckHU31G0LX1mTHZjHVfbjYeDCGBvpba/u9djU7SGc1wVh6Q6VtK5V7QPThe/fmh/yl9Vb21bcRpRT9rS5GFqRUXmyMUuojwFngrcW+r7X+I+CPAM6ePau38dKE2PUCsRSnD8iAMNEYjEz0buyL3tae6Cp7oj4OBLTWtwC/B3y28NoTwIeAk8BDwB8opcwVzvlZ4PcK5woUzg37qO8qkszw/SuzvPtUt/SziJp89L5BHrq9p27nM5sUt3Q01X1X9Lg/DlD1ZG5Dd+GJ53RISro3Yj6yfr2VYbDNxahkosVqE0D/il8fKHxtFaXU24FPA+/VWie36dqE2Be01gSiaVo2+eBYiHpZWc6922z3YLGlniitdYp8lvh9a455H/BnhX/+EvA2lf+U9j7gEa11Umt9E3i9cL6i5yy85icL56BwzvdDvu9Ka218wnuW/M18T/re5RmSmRzvOb2zpdxCQH64WL13RY/6Y7S6bbjttRXWdBbKy6UvemMWygynGWh1MRaIk8tJklAsOQccVUodUkrZyD8Uf3TlAUqpM8D/JB9Az+7ANQqxp0WSGVLZHK2y6lQ0CKOcezdmore7nLuanqilY7TWGaVUiHw5dh/5gHfla419TcXO2QYEtdaZIsevVLLvai/4+itTdDc7ODsoa3zEzjve7eFvX54gFEvjrcNgE601Y4EYR2rs+QawW820uKzMhCWIrlUmmyu63sow0ObK96qHE/RusKVA7C2F+/mvAI+Tb736U631RaXUbwEvaK0fBf4z0AT8TaHCYVRr/d4du2ghGtBm2oeMfbybbWESol52cyZ6Xw8Wq9R3tduHl4Tiaf7u6hwfuW8Qk5RyiwZwrDu/N3hoZpF7DrVu+nyheJrFRIYDVe6HXqur2SFB9AZMhRJF11sZBlrzpfWj/pgE0WKJ1vox4LE1X/vMin9++7ZflBD7iL+Q7ZMgWjQKq9mEy2bGH919mejtLueupidq6RillAXwkh8wVuq1pb6+APgK51j3s6rpu9Ja/5HW+qzW+mxHR0cNv83G8J1LM6SyOd5zR/36WoXYjFuNIHo6XJfzjQXy/dBG0FarrmYHc4tJMrlcXa5nv7g5nx8atna9lWGw1Q3IrmghhGgkgUKgIj3RopG0uGxSzl2FpZ4o8gHth4APrznmUeBjwDPAzwLf11prpdSjwBeUUp8DeoGjwPOAKnbOwmueLJzjkcI5vwar+q4e2st9V9+4MEmfz8mZft9OX4rYBrthQnR3s4Nmh6Vuw8XG/TEsJkW3d2NrEbqa7eQ0LER232qFnTS8YATRxT+I9fgcmE1KhosJIUQDWVpNKEG0aCA+l3VXlnNvaya60J9s9ERdBr5o9EQppYy+pz8B2pRSrwOfBH6t8NqLwBeBS8C3gV/WWmdLnbNwrk8Bnyycq61wbljdd3W+EKDvKYFoiqevzfOe0z1Fp+cKsROUUtza3Vy34WKjgXy5sMW0sbcyI3CWku7aDM/Hiq63MljNJvp8TkYkiBZCiIYhmWjRiCQTXaUqeqISwAdLvPa3gd+u5pyFr98gP7177df3XN/V2izkuWE/mZzecHAhxFY53u3hqy9PoLXe1AOeZCbLRCDOfYfbNnyOjiY7JgXT4QSnN3yW/Wd4IVpyvZVhoFXWXAkh9retrhDL5HJ8/ZUp7j/cVlVFlj+WwmJSJR+ACrETfC4r44Hd93lB/hbtUa+Oh2h12+j1SYmqaCynD3j5i2dHeG0izKkD3g2f58J4iExOc7DNveFzWMwm2prszIQbcx3t+bEgXc12eryNNZxreD5asRxwoM3Ft16d2qYrEkKI/Wd4Psa5YT+TwTi/9OCRisf7Iyla3OUfgNZLuQcIQqzU6rYRkHJu0QgiyQzX5yKc7vNKKbdoOO840YXFpPjGhclNnef5m34ADrZtbKiYoVEndE+HE/zNC2M81mCBaCabYywQKzlUzDDQ6iIQSxNO7L4boxBC7AbGkM6JYJwXRwIVj/fHUtIPLRqOz2UjnEiTzemdvpSaSBC9B12eDKOB2/s2nuUTYqv4XDbefLSdb1yYQuuNv2E+f9NPp8eOa5NlaV3NdgLRFKlMY03o/v7lGTRwYy5KKN44gehkMEE6W3q9lWHQWHMlE7qFEGJLXJ2JcLSziYNtLh6/OE2wQl9pIJqixSVBtGgsLS4rWtNQn3WqIUH0HvTaZL6Uu6fQH/OF50ZL/k+InfCe071MBOO8NBrc0OuzOc2LIwEOtm+8lNvQ3exAA7OLjZONngrFeW0yzKk+Lxq4ML6xf09bYXkyd4VMdKFCYEz6ooUQou780RRzkSTHujz89B29xFNZPvedq+VfE0vJjmjRcIwHO7ttuJgE0XtMPJXl+lyEk73NUsotGtY7TnZhs5g2XNJ9eSpMJJnZVD+0YXlCd+P0RX//yix2i4n339lHn8/JK2ONGERX6IkuZKJlQrcQQtTf1Zn8lovjXR56vE7uO9zGXz47wsXJUNHjM9kcM6EE7RXeu4XYbsa0eGN6/G4hg8X2mCvTYXIaTvZKKbdoXM0OKw8e6+CbF6b4tw+fwGyq7YFPvfqhIT/QwmJSDdMXfXEyxMXJMD95aydOm5k7+31889UpZsKJhthlfXM+istmrjjd1eOw0uq2MSLl3EKIfS6b00SSGbxOa93OeXVmkVa3bemB5ttv6+LqzCL//msX+Zt/ev+6RMrLY0GiqSz3HKpto4VULYqt1uLK/73YbcPFJBO9x7w2GabZYeFAS2NN8xVirffc0cvsYpJzw/6aX3tu2E+fz4mvDr1dJqXobLY3TBD9+e9ew2E18aYj7UB+mrmChslG35yPcrDNXVWlS3+rS8q5hRD73o+vz/NfnxgiXKeez3Q2x/W5CMe6PEvvxU6bmU++8xgvjASKDhl7amgWs0nxwNH/v737Do+rOhM//j0zo1Hvzerdli0X3Ds9GEyLCaETkpBAQlg2G3YJJL9ssmkbkmxISEILmIRsgBhDwEszzcZgjBvuslWsYkuyNWpWbzNzfn/MlSPbKqM6M9L7eR49nrlzy5kj+d577jnnfWNGpQxCjBYZzi08rtPuoKi6mbzEcEwylFt4uUunxxHoZx7ykG6tNTvL6lmcETVqZYkP9Y4I3QcrG3knv5rlWTEEWs2Aq0c3Oy6EfRWncI4gENtoKba1kBMf4ta6aVFBlNe3jnGJhBDCu+WfaMLu1Ow5NngEbXeU1bXS7dBMO+tcfO15SVgtJt7oI6vDpiM1zE+LHNXecCFGQ4TREz1YYDxvI43oCaSwugW7U5OXGObpoggxqCCrhYunx/HWgZPYHe5Hxi6pbaW2pYuFo9mIDgugqcPu8RP40x+VEBpgYVnWmT0Fc1IiaGjr9nik67YuOxUN7WTHuteITo0KMqJ5e1fkcyGEGC8d3Y7TI3J2lTeMKCtFj8KTzVhMioyYM8/FIf4WLpway5sHTuDslS7oZGMH+SeaiAyySpBZ4XVC/C1YTIr6Vt8azi1zoieQg5WNBFvNoxKxWIjxuLBePTuBN/afYFtJHStzYt3aZqcxH3phetTpudEjNcWIZF9wspnFmUObLzZa7A4nHxyxsSpvyule6B55CWG8Zlbs9XCU7pIaV69ydlyIW3OXMmKCcTg1x+rbyHKz4S2EEBNJSU0LTg3z0yLZXd5AWV0bGSO8TyuobiEjJhir5dy+sCtnJ/BOfjW7jzWwMN31sPnDQhvgCkImhLdRShEZbPV4R8ZQSU/0BNHtcFJQ3cyMxDAZyi18xoXT4gi2mtmw1/0h3TvK6okOtpIVO3oPi3rSwe314LzjPcdP0dRh56Jpced85u9nZnpCGAcqGj2az7rY1gK4GtHuyDR+Rz2NbyGEmGwKbS1YLSZWz0zA32Ji1zDigPRW39pFrZHaqi+XTHdlv3hj/z+HdG86UkN4oB/xYQOnJhTCUyKD/GROtPCMYlsLXXanROUWPiXAz8zn5ybxyp5K8qua3NpmZ1k9C9IjRzWFW2iAHzEh1mEFOTtbR7eDE43tQ97ugyM2LCbFyql9B305LzmC9m4HnxytHWkRh63I5hpCmOZmarFMo/e5pKZlLIslhBBeSWtNUXUzmTHBBFrNzEmO4GBVIx3djmHvs6AntdWUvhvRIf4WLpr2zyHdXXYnHxfXnhGETIix0NdUAXenDEQEWX0uOrcM554gDlU1EuBnOt3zI4Sv+I9V09h46CQPvbKfV+5ZPmC6qxON7Ryvb+eOpemjXo706GB2ljXgdGpMQ0y51dvLn1VwqKqJOcnhXDk70e3tNh2xsSA9krCAvoO+ZMaGYFaKT0vqubCP3urxUGxrIS06qM8hhH0JD3Q9nJCeaCHEZFTf2kVDWzcrjOlKC9Ij2VFWz75BpuYM1Og4cqKJqGArMSH99ypfOTuRjYeq2VXecDq9lgzlFt4sMsjP5+4VpBE9AdgdTg6faCZ3ShgWkwwu8CYSsGNwEUFW/vPqPO57YQ/3vbCH5dln9sTesjj19OueOdCLh5jn0h3pMcHsKm+g0Ob6vzQcJxrbOVTVRGpUEAcrmyisbiEi0I8vLkgesAeg6lQ7R04289AVuf2uY7WYSIwIGPFQwJEosrWQ4+ZQ7h6ZMSGU1EpPtBBi8ik0psBMNc6bSRGBTAkL6DMFlTt2l9dTZGvhczPiB1zvktw4/C0m3jxwAn+LCT+zIitOOlmE94oMstLQ5h2pPN0lLa4JYHd5A+3dDqYnSFRu4Zuunp3AtPhQ3s2v7ndOTLfDyZ8/KSM80I/pCaP/RD3dGKK8cwTByjYdseFvMXHH0nTuvTibuDB/Hnh5Pz/ccGjg7QpcQV8uzh24hzk9Jpj9FSMbCjhcXXYn5XVt5MQNre4zY4N97umyEEKMhqLqZqKCrUQbvcZKKeanRVLR0M7hE+5NYepRdaqd1/ZWkRUbzAVTBw7EGexv4aJpcbxx4ATvH7GxKCMKf4t5wG2E8KSewGKjEb1+vEgjegJ473A1ZpM6/aRTCF+jlOLa81xDn1/bW9nnSfRXGwvYc+wUP1szE4t59E9dkUF+TAkLYPswG9Enmzo4WNXEsqxoAq1m4sMC+PrKTG5amMLz249R0dB/eqpNR2pIjgwcNGBXenQwXQ4n+zwQAK28rhWHU7sdVKxHZmwwda1dPhd1UwghRqLL7qSktvWcc+bclAjMJsXfdx53e1/tXQ7+tr2cYH8LNy5MdSuA7OrZCdQ0d1Jsa+kzYKUQ3iQyyA+7MfXAV0gjegJ4/7CNzJhg/P3kKaPwXRFBVj43I57C6hY2Fdhw9mpIv5dfzVNbSrh9SRpXDWGe8VAopViUEcXOsvphPQnt6YXuPRzdpBT3XZKDUvCnLSV9btfR7WBrcS0XTYsbNOhLWnQQwKgEQBuqoiFG5u6RaeQxPSq90UKISeSzYw102Z3ndHAE+VuYkRDGhn1VbmVbcGrNul3HaWq3c/OiVEL83ZuJ2TOkG/BYHA0h3BURZAXglA8FF5NGtI87WtNCSW0ruTKUW0wAS7OimZkYxnuHbTzx4VFONnZQ0dDG/S/tIy8xjO9fOX1Mj78wI4rqpk6O1fffa9yX6qYODlY2sjQzmiDrmTc4iRGBXDc3mRd3HqemufOcbXeU1tPe7Rh0KDdAkNXCtPhQdpQNbz7dSBTbWlCKIed7zoqTCN1CiMlnS2ENJvXPLAW9zU2NoL61iw8Lawbch9aajYdOUlDdzOrZCaRGBbl9/GB/C5fPnEJ2XMiopoQUYixEGo3o+lbfGbUmjWgf9/7hagBy+0l1IIQvMSnFzYtSuWlhCg2tXfxhUxE3PfUpTqfmsVvnETDGoy0WpUcB/wxg5q5NBTb8LCZWZPednuruCzLpcjhZu7X0nM8+MHqwl2a5FyxtYUYknxkRV8dTsa2FpIhAAq1D+x2kRAbiZ1aU1EpPtBBi8thSVENqVFCf162cuFBiQqy88llFv9trrXn9wAk+KqplcUYUSzKihlyGh78wm5e/uUxSWwmvFxfqihtwfICpb95GGtE+7r18G9MTwk4/wRHC1ymlmJ0cwbcvncrs5AiqTrXzy+tnu52beCRy4kKICPIb0nDpYlsLByqMXuh+htllxoawelYCf91WTmP7P4cqaa3ZVGBjWVa02w8IFqZH0dJpH3JQmpEqsrUMeSg3gMVsIjUqSHqihRCTRl1LJwcrm8juJxCj2aS4Zk4S7x+20djH8FWn1vxjTyXbjtaxPCuaa+YkDqshHOBnJjyw77SJQniTGYlhhPpb+Lio1tNFcZs0on1YQ2sXu8rruXS6zHURE0+wv4UbFqRw4EeruGJWwrgc02RSLEiLGlJP9FNbjmIxq3NSc53tnguzaOm089dtZaeX7atopLyuza2h3D0WDrO3fCQcTk1JzdDTW/XIjA2RCN1CiEnj42JXQ2BqfP/nzOvmJdHlcPL6gaozltsdTl7adZxd5Q1cNC2O1bMSpCdZTHh+ZhMrcmLYXFDjMxG6JU+0D3MFX4JLp8dzqGp8e6WEb/HlfNXBbgZRGS2LM6J473A1tuYO4kIDBly3uqmDf+ypZH5a5KDBXvISw7loWixrt5ahlOKtgyc4WNlEkNXMJdMHzvnZW2JEIEkRgewsq+erKzLc3m4kKhva6bQ7h9UTDa4I3R8W1OBwaswmuRkUQkxsWwpriQzyIzEisN918hLDmBofwiufVXLr4rTTy3+1sYB9FY2sypsyaCorISaSC6fF8tbBkxRWtzDNB6apSk+0D3v/sI3YUH9mJYV7uihCTBgLjXlnO0sHD961dmspDqdmRbZ7Nzrfuiib+tYufrWxAIvJxPdW5/LOv50/4I1WX0YSRXw4imzNwNAjc/fIigmhy+EcMM2XEEKMlue3H+vzZzxorfmoqIbl2TEDpqJSSnHdvGR2lzdQZsSMeDe/mie3lLA4I0oa0GLSOd/4m99cYPNwSdwjjWgf1WV38mFhDZdOj8MkPTtCjJq8xDAC/czsKK0bcL2mjm6e//QYq2clEBXsXkyCBelRrLt7KVsfvJhXv7Wcu87PIjnS/WirPRamR1Hb0kVZ3fg0Sot70lvFDu/JcKYRGVaGdAshJrrC6hZszZ2cnzN4I/jz5yWhFLyyp5Lj9W3cv24vM5PCWD1OU5iE8CYJ4YHkTgllc8HAUeu9hTSifdT20jpaOu1ckuv+MFAhxOD8zCbmp0UOmkbqhe3HaO60c/f5WUPa/6KMKJKG2PN87j4iAdg5TvOii20txIb6Ex40vAA1PSlejkpwMSHEBPdRkasBsCJn4DgZAFPCA1ieFcMrn1Vw7wt70MBjt8zHzyy352JyumBqLLvK62nptHu6KIOSOdE+6t38agL8TIMGMxLC13liPveSzCj+591Cdpc3MD8t8pzPO+0O1m4tZXl2NLOSwzlQ2Tiu5cuKDSEq2MqOsnpuWJgy5scrsrWQPcT80L1FBVuJCPKTNFdCiAlvS1Et2XEhbk/TuW5eEt9Zt4+KhnaeuG0+qdFBUDzGhRTCS10wLZYnt5TwSXEtl+VN8XRxBiSPunyQw6l56+BJLpoWN+ScrUKIwd2+NJ2UyCDuff4z6lu7zvn8tT1VVDd1DrkXerQopViQFjmkVFzDpbXm6DDTW/WWFRsiaa6EEBNaR7eD7SV1rHSjF7rHqrwpJEUEcs+FWVw+07sbDUKMtQVpUQRbzXxY6P1DuqUn2of09MiV1LZQ09xJeKCfT0ddFsJbhQf68dit87jusU/4zrq9rL1j4enYA5Wn2nlsczHTE8KGdKM02lbkxPBOfjXbjtaxNCt6zI5ja+6kudNOzgCpWtyRGRPMZh+4KAohJpZtR2uxOzVTwgKwNXcQG+I/rJRRh6oaeWlXBfdfNpXQgL6ntuwsq6fT7nRrPnSPYH8LWx64SDIXCAFYLSaWZf8z1ZU3p3eTRrQPOlDRiJ9Z+UT4dyF686WHPjOTwvnB1TP4wasHefzDo3zzgiye33GM/37zME4NT94+06Mn9xsWpPDE5qP87M18NnxrxZgFGCyq7gkqNsJGdGwIL+2uoLmju98bUCGEGE2VDe383/4Tp98/+0kZyZGB/O+di0mPCXZ7P/srTnHb09tp6rBT09zJH26Z2+f5/6OiWqxmE4szo4ZUztFqQPvSNVaIHmf/3QZZzVSeaud37xfx7UuneqhUg5NGtI9xas2hqiamxYfib5Gh3EKMpdsWp7KjtJ7/eaeAd/Or2Xv8FMuzo/nFdbNJiRp6VO3RFOBn5j8un8a//X0fr+2rZM3c5AFvoG5ZnDqs42wpqsFsGvlDu94RuuekRIxoX0II4Y5PS+qwmk3cd0kOp9q6SIwI5OG3j/D45qM8fP1st/ax51gDX1q7g/BAP25cmMKfPipl3tZI7lyRcc66WwprWJAeSZBVbq+FGK6p8a77jcJq754CJv/LfUxZbSstnXZmJctNqBBjTSnFf183i0NVjRy1tfCL62Zx48IUrxledO2cJNZ+XMav3i7gipmjnxKlpdPOCzuOccXMKUSH+I9oX1k9jejalnFrRI/FQwUhhG9o67Szr+IU89MiiQq2EhVs5ZbFqZTUtrBuZwXfuWwq8WEBA+5jd3k9d6zdidVi4pZFqYQH+jEjIYyfvZGPramDtOjg0+cSW1MHR042893Lc8fj6wkxYUUGWYkN9aewutnTRRmQNKJ9zIFKYyh3vAzlFmK09dfoum1xGl+YlzzsFE9jxWRSfP/K6dz01Kc883EpkUHu5at210u7jtPcYedrKzNHvK/UqGDMJiW5ooUQ42JXeQN2p2ZJ5pkxI+5amcXz24+xdmspD10xvd/tj9e3ccfancSG+nPDghTCA13n/y/MS+aPm4t5Yccx7r045/T6HxfXAng0VoYQE8W0+FC2ldRR3dQx6MMuT5Ho3D7E4dQcrGoid0oYVov86oQYLwF+Zq9rQPdYkhnN52bE89imYpo7ugHXuaKxvZvalk5sTR2caGyndIjppRxOzdqtpcxPi+S8Ueg5tlpMpEQGSiNaCDHmnFrzaWkdmTHB59yAp0YHsXpWAs9/eowm45zZl5+8no/DqXnuq4tON6ABAq1mbl2cSluXgyc+PMqDL+/nr9vKeG1vFdHBVmYkhI3V1xJi0liSGY3WmkffL/J0UfolPdE+pKyuldZOO7OSwj1dFCG83mgHWPHmgC0PXZHLZY9s4Y+binFo1zBGfdY6v/+gmCtnJfCja/KIDR18aPa7+dUcr2/newP01AzV7OQIPiqqocvulAeBQnjQRJ/qUHCymVNt3azuZ5rLNy7I4vX9J3h++zG+ccG5qQo3F9h4J7+a/1g1rc/4FwnhgdyyKJWPj9by1sGTvLjzOABr5iaNWZBHISaTqGArC9Oj+PvO43x9ZeaQAgGOF2lE+5ADFY1YzabTE+6FEAJcka+/f+V0/r7zOKEBfoQFWAgN8MNqUZiU6ycuzJ/HNh/l4+JafnDVDL4wL2nAud3PfFxCSlQgl+WNXt7SNfOS2LCvig+O2CQfqhBizGwrqSM80I/p/fQKz0wKZ0V2DGs/LuUry9PPCNTaaXfwow2HyIgJ5msrzw0e1iM3IYzchDBuXpRCVWMHhSebmZXsfieHNz+YFcIbXJQbx76KU/zm3UIevXmup4tzDmlE+wi7w8nBqkZyE0KlB0cIcY6vLM8YMGL/LYtTuWp2Ig++vJ9/f2kfr+2t5MfXziSjj6e7+46fYmdZAz+4asao5i5dmR1DXKg/63dXSCNaCDEmim0tFNta+NyM+AHPX3dfkMntz+zg1T2V3Lgw9XSjdlOBjbK6Nr68LJ2Xd1cOejylFEkRgSRFBI7adxBCQFiAH19dnsFjm49y9wWZ5CV610hcaY35iI+KamnrcshQbiHEsGXHhbDu7qX85No89h47xapHtvCbdwro6Hacsd4zH5cS6m/hhgXJo3p8i9nEmnlJbC6wUdvSOar7FkKMTJfdybaSOm5+6lMOVDR6ujjD9szHpZhNioXpA+dqXpEdQ15iGL/aWMAv3z5CaW0rdS2dbC6wkZcYJqP+hPACd5+fRViAhV9vLPB0Uc4hPdE+wOnU/PqdAiKC/CQqtxATiBZqGSkAABI2SURBVCeG85lMituXprMqbwo/f/Mwj35QzD/2VrIkI5ryujZK61qpae7kaysyCA0Y/WBq189L5skPS3htb1WfeVbHUmunnXfzq9l9rIEdpXV8b/V04rw06qcQ46WpvZtPjtaxo6yOjm6nK6/yi3t4474V45Lv+Pntx2jvcpB/otEVxDHQj/BAP4L9Ldy2JG1I+3ptbyUv7DjG0sxoQvwHLrtSip+vmcXP3jzMk1tKcDg1CrCYFVfOcj9loAzLFmLshAf58c0Ls3n47SPsKK1nUcbAD8fGkzSifcCGfVUcqmrihgXJWMwyeEAIMXJxYQH89qa53LAwhfvX7ePtgyeJDrGSGhnE/NRIkiPPDaYzGnLiQ5mTHM763RXj1oh2ODU7yup5L7+aTruD3ClhvHngJO8dtvHtS3O4Y1k6fnJuFZNQa6ed328qpq3TTl5iGCuyY7gwN46b//QpP33jMD9fM2vMy9DY3s2zW0uxNZ85OiUmxMrc1Ai3h3DuO36KB9bvZ1F6FFfMcm+6yJyUCNbdvZSmjm5+8eYRimzNZMQEEzHK6QKFEMP35WXpPLu1lP9+6zCvfHPZgPFcxpM0or1cR7eDX20sIC8xjNnJI08zI4QYX94eJXxZVgz/0ivX6Xi4fn4yP3jtEIeqGsd8jlNrp52/bCujoqGdzNhgrp6dSHxYAMuyovmv/zvET984zPrdFfz1zsVuRS0XYiJ588AJ2rvs3HNhNkmRrjm9SzKjuWtlJk9uKeGS3DgumR4/ZscvtjXzxIdH6eh28KWlaYQG+NHY1s2p9i62FNZw3WOf8JNrZ3LDwpQB91Pd1MHXn9tFbKg/j982j42HqodUjrAAP2YmhTNTpswJ4XUCrWb+/bJpPPDyfl7dW8mauaM71Wy45NG7l/vrtnIqT7XzvdXTMXnJkxchhBiJq+ckYjWbWL+7YkyP09ZpZ+3WUk42dnDjghTuXJ5xOmdsekwwa7+8kCdvn095XRu3P7Odxrb+c8YKMdEUVjez5/gpLpgad7oB3eM7l00ld0oo3315/5jFL/jsWAPXP7ENh1Pz9ZWZ5E4JIykikBmJYSzLiuHei3NYkB7JAy/v54H1+2jvcvS5n9ZOO3c9t4vWTjtP37GA6BB5GCbERHP9/GRmJ4fzi7eO0Npp93RxAOmJ9mqNbd38YVMx50+NZXl2DOV1Mu9GCDE83jRvLyLIyqUz4nhtbxUPXTF9TDIONLR28czWUmqaO7ltSVqfQYKUUqzKm8JTX5rPnX/exR3P7uB/v7Z40LmUQvi6TruDV/dUEhviz0XTYs/53N9i5rc3ncc1v9/KA+v389it8wjwMw94Hvn83EQ6u51EBg88FFprzd+2H+Onb+QTFxrAF+cn99nwDfG38NxXF/Pb9wr5/QfFvL7/BBdOi+WyGVNYkhnN7vIG3jxwgg+O2OiwO3jytvnkTuk7pVUPbzoPCiHcZzIpfnRNHtc99gl/3FTMA5fnerpI0oj2Zo9tLqapo5sHveAPRQgx+YzlDef185N588BJXtp9nFsXDy140GBOtXVx2zPbB2xA97YyJ5bf3zKXe/72GV//yy6e/cpCAvz6TxcmhK97N7+aU+3d3H1+Zr+xVnKnhPG91bn86P/yWf27j/jpmpmnP3M4NfknmtheUkddaxdtXXa+948DAKzMieEbF2SxLCv6nLmLtS2dPPjyft47bGNlTgy/ueE83s3vf+j133ceJyE8kLvPz2TP8VN8VFTLmwdOnv482N/CrORw5qZEUNvSJY1kISaweamRXDc3iac/KuXGhSmkRZ+bonM8jXsjWil1OfA7wAw8rbX+xVmf+wPPAfOBOuBGrXWZ8dlDwJ2AA7hPa71xoH0qpTKAF4FoYDdwu9a6a6BjeAOHU/Onj0pYu7WUNXOTmJE48JNVIYTwJgPdyN6yOBWA83NimZMSwff/cZDPyk/xn1fPIDxwZNHA7Q4n63dX8Mh7hTS0drvVgO6xKm8Kv/7ibL6zbh+3P7Odn6+ZRY5kQxhVI7n+i9Gzs6yebUfrWJwRNehN6JeXZ5AZG8L/e/Ugt/xpO/NSI0kID+CTo7U0tHUTFWwlKzaEYKuZZdkxtHc7eH77MW59ejszk8K4bm4yVosJrTXt3Q6e2lJCU4edH149gzuWpmNyMw99WnQwadHBXDMnkYqGdspqW0mODCQ9JlimugkxiXz3ilzePnSSn75xmD99aYFHyzKujWillBn4I/A5oALYqZTaoLXO77XanUCD1jpbKXUT8DBwo1JqBnATkAckAu8ppaYa2/S3z4eBR7TWLyqlnjD2/Xh/xxjbb++estpW/v2lfewqb+DyvCn88Ko8TxdJCCFGncVs4qW7l/L7D4p4bPNRthbX8rM1M1meHTPkXuCObgcfFtbwq40FFNtamJcaweO3zefIieYh7WfN3GRMSvGfrx3iit99xJ0rMrjvkhyCZXj3iI3k+j/+pZ2Ymjq6efS9Iv78SRnhgX6synMvgvX5U2PZ+O3zefSDIp788CifHYO06CBWz0pgekLY6UZszwOyey7M4tU9lTy1pYQfv55/xr6mhAXwjQuy8LeYeXHn8SF/B5NSpEYFkRo1NtkDhBDeLT4sgHsvzuaXbxfw6PtF3LEsfcQP4IdrvO8MFgHFWusSAKXUi8C1QO+z7LXAj4zX64E/KNd4oGuBF7XWnUCpUqrY2B997VMpdRi4GLjFWOcvxn4f7+8YWms9qt92AFprHE5Nc4ed0rpWSmtaKaxu5rlt5VjMikdunMPnz0vymjDuQggx2qwWE/dfNo1Lp8dz/0v7uPMvuwCID/MnNSqIuNAALGaF2aSwmBRag0NrnE5Nt1NzsrGD4/Vtp1PjZMYG88Rt81mVF49SasiNaIBrz0tiRXYMD799hCe3uPJZr56VwNT4EHLiQ5kaHzIm+bMngWFf/8fz2jyRdDucNLZ309jezc7Sen79TgF1rV3cuCCFzNiQIT2sCrSa+e7luQT5melyOEkID+x33QA/MzctSuWGBSnUtHSigFf3VqGM/UjPsRBiJO5ckcGO0np+824hT3x4lC/OT+YryzNIjxnf4d3j3YhOAno/eqwAFve3jtbarpRqxDUcOwn49Kxtk4zXfe0zGjiltbb3sX5/x6gd9jdzw+7yBm57ejt2p5Nux7n3BGaT4oKpsfxszcwBL1BCCOGr+hvqffuSNPKrmqht7aShtYua5i7Kattwao3TeOiolEIpV2+USUFogB/JkUHMSg4nPjSA6Qlh1Ld28cKOofdw9RYd4s8vr5/DjQtT+eXbR3h+Rzkd3c7Tn7/8zaXMT4sa0TEmoZFc/8f02ryzrJ4vr91xxrLeV2h3mvBntwvdbSaeveuhPi7oOW7PdtrYo1NDl915xrrz0yJ59suLmJUcPuCUi4E+Gyjy9UDbSbA+IcRo8beY+fNXFnGwspG1W0t5fscxnvu0nPXfGN9rs5zVBqCUugu4y3jbopQqGOtjlgDPfuX02xjG+OZhkpJ6HRtSr2ND6nUM3DqCel3w8KgVY3Qjqk0SI7w2T9r/T+XAK/eMeDeTtv5GgdTd8EndDZ9P192tQ1h3wS8GX8dNbl2bx7sRXQmk9HqfbCzra50KpZQFCMcVYGSgbftaXgdEKKUsRm907/X7O8YZtNZPAU8N8TuOGqXULq21Z2fNT0BSr2ND6nVsSL2ODanXcTeS6/8ZRnJtlt/7yEj9DZ/U3fBJ3Q2f1N3YGf3knAPbCeQopTKUUlZcgcI2nLXOBuAO4/X1wAfGfKgNwE1KKX8j6nYOsKO/fRrbbDL2gbHP1wY5hhBCCCFG30iu/0IIIYRXGdeeaGOO073ARlwpLtZqrQ8ppX4M7NJabwCeAf5qBA6rx3WhxVhvHa4gJHbgW1prB0Bf+zQO+V3gRaXUT4E9xr7p7xhCCCGEGH0juf4LIYQQ3kbJQ17vpZS6yxi2JkaR1OvYkHodG1KvY0PqdXKS3/vISP0Nn9Td8EndDZ/U3diRRrQQQgghhBBCCOGm8Z4TLYQQQgghhBBC+CxpRHsppdTlSqkCpVSxUupBT5fH2yil1iqlbEqpg72WRSml3lVKFRn/RhrLlVLqUaMu9yul5vXa5g5j/SKl1B29ls9XSh0wtnlUqbOzgE5MSqkUpdQmpVS+UuqQUupfjeVStyOglApQSu1QSu0z6vW/jOUZSqntRl383Qi4hBFA8e/G8u1KqfRe+3rIWF6glFrVa/mkPGcopcxKqT1KqdeN91Knok9KqQil1Hql1BGl1GGl1FJPl8kXKKWmKaX29vppUkp929Pl8hVKqX8zzvsHlVIvKKUCPF0mX6GU+lej3g7J39zghnJvLEZOGtFeSCllBv4IXAHMAG5WSs3wbKm8zp+By89a9iDwvtY6B3jfeA+ueswxfu4CHgfXiQX4IbAYWAT8sNfJ5XHg6722O/tYE5UduF9rPQNYAnzL+NuTuh2ZTuBirfUc4DzgcqXUEuBh4BGtdTbQANxprH8n0GAsf8RYD+N3cROQh6veHjMakZP5nPGvwOFe76VORX9+B7yttc4F5nDm343oh9a6QGt9ntb6PGA+0Ab8w8PF8glKqSTgPmCB1nomrqB6EjDPDUqpmbjuFRbh+v96lVIq27Ol8np/xv17YzFC0oj2TouAYq11ida6C3gRuNbDZfIqWustuKK39nYt8Bfj9V+Az/da/px2+RRX/vAEYBXwrta6XmvdALyLq3GTAIRprT810qs812tfE5rW+oTW+jPjdTOum8wkpG5HxKifFuOtn/GjgYuB9cbys+u1p77XA5cYPfbXAi9qrTu11qVAMa7zxaQ8ZyilkoErgaeN9wqpU9EHpVQ4cD5Glg6tdZfW+pRnS+WTLgGOaq3LPV0QH2IBApUr93kQUOXh8viK6cB2rXWb1toOfAhc5+EyebUh3huLEZJGtHdKAo73el9hLBMDi9danzBenwTijdf91edAyyv6WD6pGMNd5wLbkbodMaN3cy9gw/VQ4Shwyrg5gDPr4nT9GZ83AtEMvb4nut8CDwBO4300UqeibxlADfCsMfz/aaVUsKcL5YNuAl7wdCF8hda6Evg1cAw4ATRqrd/xbKl8xkFgpVIqWikVBKwGUjxcJl/U3/2bGCFpRIsJyejllNDzw6SUCgFeBr6ttW7q/ZnU7fBorR3GcMhkXL2cuR4ukk9TSl0F2LTWuz1dFuETLMA84HGt9VygFRnWOCRGfIFrgJc8XRZfYUxjuhbXQ5xEIFgpdZtnS+UbtNaHcU27eQd4G9gLODxaKB8n92+jSxrR3qmSM5+2JRvLxMCqjeHCGP/ajOX91edAy5P7WD4pKKX8cDWg/6a1fsVYLHU7SowhpJuApbiGv1uMj3rXxen6Mz4PB+oYen1PZMuBa5RSZbiGWl+Ma86r1KnoSwVQobXebrxfj6tRLdx3BfCZ1rra0wXxIZcCpVrrGq11N/AKsMzDZfIZWutntNbztdbn44pxUejpMvmg/u7fxAhJI9o77QRyjCizVlzDpzZ4uEy+YAPQEwX6DuC1Xsu/pFyW4BpOdQLYCFymlIo0nhZfBmw0PmtSSi0x5kx+qde+JjTj+z4DHNZa/6bXR1K3I6CUilVKRRivA4HP4Zpvvgm43ljt7Hrtqe/rgQ+MJ8gbgJuMSNMZuAKz7WASnjO01g9prZO11um4vu8HWutbkToVfdBanwSOK6WmGYsuAfI9WCRfdDMylHuojgFLlFJBxjXvEiSgnduUUnHGv6m45kM/79kS+aT+7t/ECFkGX0WMN621XSl1L66GiBlYq7U+5OFieRWl1AvAhUCMUqoCVyToXwDrlFJ3AuXADcbqb+KaS1OMK6roVwC01vVKqZ/gulkG+LHWuicgwz24ohwGAm8ZP5PBcuB24IAxfxfge0jdjlQC8Bcj4rMJWKe1fl0plQ+8qJT6KbAHI+iR8e9flVLFuIKE3ASgtT6klFqH6+bfDnxLa+0AkHPGad9F6lT07V+AvxkPRUowzldicMb88c8Bd3u6LL5Ea71dKbUe+AzX+WUP8JRnS+VTXlZKRQPduM7NEgxwAEO8NxYjpFwP4oUQQgghhBBCCDEYGc4thBBCCCGEEEK4SRrRQgghhBBCCCGEm6QRLYQQQgghhBBCuEka0UIIIYQQQgghhJukES2EEEIIIYQQQrhJGtFCCCGEEEIIIYSbpBEthBBCCCGEEEK4SRrRQgghhBBCCCGEm/4/fH7sEq0NMPoAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 1152x864 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Ploting Transaction Amount Values Distribution\n",
    "plt.figure(figsize=(16,12))\n",
    "plt.suptitle('Transaction Values Distribution', fontsize=22) \n",
    "plt.subplot(221)\n",
    "sub_plot_1 = sns.distplot(data_train['loanAmnt']) \n",
    "sub_plot_1.set_title(\"loanAmnt Distribuition\", fontsize=18) \n",
    "sub_plot_1.set_xlabel(\"\") \n",
    "sub_plot_1.set_ylabel(\"Probability\", fontsize=15)\n",
    "plt.subplot(222)\n",
    "sub_plot_2 = sns.distplot(np.log(data_train['loanAmnt'])) \n",
    "sub_plot_2.set_title(\"loanAmnt (Log) Distribuition\", fontsize=18) \n",
    "sub_plot_2.set_xlabel(\"\")\n",
    "sub_plot_2.set_ylabel(\"Probability\", fontsize=15)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "非数值类别型变量分析"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['grade', 'subGrade', 'employmentLength', 'issueDate', 'earliesCreditLine']"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "category_fea"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "B    233690\n",
       "C    227118\n",
       "A    139661\n",
       "D    119453\n",
       "E     55661\n",
       "F     19053\n",
       "G      5364\n",
       "Name: grade, dtype: int64"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_train['grade'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "C1    50763\n",
       "B4    49516\n",
       "B5    48965\n",
       "B3    48600\n",
       "C2    47068\n",
       "C3    44751\n",
       "C4    44272\n",
       "B2    44227\n",
       "B1    42382\n",
       "C5    40264\n",
       "A5    38045\n",
       "A4    30928\n",
       "D1    30538\n",
       "D2    26528\n",
       "A1    25909\n",
       "D3    23410\n",
       "A3    22655\n",
       "A2    22124\n",
       "D4    21139\n",
       "D5    17838\n",
       "E1    14064\n",
       "E2    12746\n",
       "E3    10925\n",
       "E4     9273\n",
       "E5     8653\n",
       "F1     5925\n",
       "F2     4340\n",
       "F3     3577\n",
       "F4     2859\n",
       "F5     2352\n",
       "G1     1759\n",
       "G2     1231\n",
       "G3      978\n",
       "G4      751\n",
       "G5      645\n",
       "Name: subGrade, dtype: int64"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_train['subGrade'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "10+ years    262753\n",
       "2 years       72358\n",
       "< 1 year      64237\n",
       "3 years       64152\n",
       "1 year        52489\n",
       "5 years       50102\n",
       "4 years       47985\n",
       "6 years       37254\n",
       "8 years       36192\n",
       "7 years       35407\n",
       "9 years       30272\n",
       "Name: employmentLength, dtype: int64"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_train['employmentLength'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2016-03-01    29066\n",
       "2015-10-01    25525\n",
       "2015-07-01    24496\n",
       "2015-12-01    23245\n",
       "2014-10-01    21461\n",
       "2016-02-01    20571\n",
       "2015-11-01    19453\n",
       "2015-01-01    19254\n",
       "2015-04-01    18929\n",
       "2015-08-01    18750\n",
       "2015-05-01    17119\n",
       "2016-01-01    16792\n",
       "2014-07-01    16355\n",
       "2015-06-01    15236\n",
       "2015-09-01    14950\n",
       "2016-04-01    14248\n",
       "2014-11-01    13793\n",
       "2015-03-01    13549\n",
       "2016-08-01    13301\n",
       "2015-02-01    12881\n",
       "2016-07-01    12835\n",
       "2016-06-01    12270\n",
       "2016-12-01    11562\n",
       "2016-10-01    11245\n",
       "2016-11-01    11172\n",
       "2014-05-01    10886\n",
       "2014-04-01    10830\n",
       "2016-05-01    10680\n",
       "2014-08-01    10648\n",
       "2016-09-01    10165\n",
       "              ...  \n",
       "2010-01-01      355\n",
       "2009-10-01      305\n",
       "2009-09-01      270\n",
       "2009-08-01      231\n",
       "2009-07-01      223\n",
       "2009-06-01      191\n",
       "2009-05-01      190\n",
       "2009-04-01      166\n",
       "2009-03-01      162\n",
       "2009-02-01      160\n",
       "2009-01-01      145\n",
       "2008-12-01      134\n",
       "2008-03-01      130\n",
       "2008-11-01      113\n",
       "2008-02-01      105\n",
       "2008-04-01       92\n",
       "2008-01-01       91\n",
       "2008-10-01       62\n",
       "2007-12-01       55\n",
       "2008-07-01       52\n",
       "2008-05-01       38\n",
       "2008-08-01       38\n",
       "2008-06-01       33\n",
       "2007-10-01       26\n",
       "2007-11-01       24\n",
       "2007-08-01       23\n",
       "2007-07-01       21\n",
       "2008-09-01       19\n",
       "2007-09-01        7\n",
       "2007-06-01        1\n",
       "Name: issueDate, Length: 139, dtype: int64"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_train['issueDate'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Aug-2001    5567\n",
       "Aug-2002    5403\n",
       "Sep-2003    5403\n",
       "Oct-2001    5258\n",
       "Aug-2000    5246\n",
       "Sep-2004    5219\n",
       "Sep-2002    5170\n",
       "Aug-2003    5116\n",
       "Oct-2000    5034\n",
       "Oct-2002    5034\n",
       "Oct-2003    4969\n",
       "Aug-2004    4904\n",
       "Nov-2000    4798\n",
       "Sep-2001    4787\n",
       "Sep-2000    4780\n",
       "Nov-1999    4773\n",
       "Oct-1999    4678\n",
       "Oct-2004    4647\n",
       "Sep-2005    4608\n",
       "Jul-2003    4586\n",
       "Nov-2001    4514\n",
       "Aug-2005    4494\n",
       "Jul-2001    4480\n",
       "Aug-1999    4446\n",
       "Sep-1999    4441\n",
       "Dec-2001    4379\n",
       "Jul-2002    4342\n",
       "Aug-2006    4283\n",
       "Mar-2001    4268\n",
       "May-2001    4223\n",
       "            ... \n",
       "Feb-1962       2\n",
       "Aug-1950       2\n",
       "Sep-1961       2\n",
       "Jul-1961       2\n",
       "Sep-1959       2\n",
       "Nov-1962       2\n",
       "Apr-1955       2\n",
       "Jul-1955       1\n",
       "Nov-1954       1\n",
       "Aug-1958       1\n",
       "Feb-1960       1\n",
       "Jan-1946       1\n",
       "May-1960       1\n",
       "Mar-1958       1\n",
       "Jun-1958       1\n",
       "Mar-1957       1\n",
       "Sep-1953       1\n",
       "Oct-1957       1\n",
       "Sep-1957       1\n",
       "Dec-1951       1\n",
       "Nov-1953       1\n",
       "May-1957       1\n",
       "Mar-1962       1\n",
       "Jan-1944       1\n",
       "Aug-1946       1\n",
       "Aug-1955       1\n",
       "Apr-1958       1\n",
       "Oct-2015       1\n",
       "Dec-1960       1\n",
       "Oct-1954       1\n",
       "Name: earliesCreditLine, Length: 720, dtype: int64"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_train['earliesCreditLine'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    640390\n",
       "1    159610\n",
       "Name: isDefault, dtype: int64"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_train['isDefault'].value_counts()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 总结:\n",
    "1. 上面我们用value_counts()等函数看了特征属性的分布，但是图表是概括原始信息最便捷的方式。\n",
    "2. 数无形时少直觉。\n",
    "3. 同一份数据集，在不同的尺度刻画上显示出来的图形反映的规律是不一样的。python将数据转化成图表，但结\n",
    "论是否正确需要由你保证。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 变量分布可视化\n",
    "单一变量分布可视化"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 576x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(8, 8)) \n",
    "sns.barplot(data_train[\"employmentLength\"].value_counts(dropna=False)[:20], data_train[\"employmentLength\"].value_counts(dropna=False).keys()[:20])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "根据y值可视化x的分布"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [],
   "source": [
    "train_loan_fr = data_train.loc[data_train['isDefault'] == 1]\n",
    "train_loan_nofr = data_train.loc[data_train['isDefault'] == 0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1080x576 with 4 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ((ax1, ax2), (ax3, ax4)) = plt.subplots(2, 2, figsize=(15, 8)) \n",
    "train_loan_fr.groupby('grade')['grade'].count().plot(kind='barh', ax=ax1, title='Count of grade fraud')\n",
    "train_loan_nofr.groupby('grade')['grade'].count().plot(kind='barh', ax=ax2, title='Count of grade non-fraud') \n",
    "train_loan_fr.groupby('employmentLength')['employmentLength'].count().plot(kind='barh', ax=ax3, title='Count of employmentLength fraud') \n",
    "train_loan_nofr.groupby('employmentLength')['employmentLength'].count().plot(kind='barh', ax=ax4, title='Count of employmentLength non-fraud')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x11b052190>"
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1080x432 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ((ax1, ax2)) = plt.subplots(1, 2, figsize=(15, 6)) \n",
    "data_train.loc[data_train['isDefault'] == 1]['loanAmnt'].apply(np.log).plot(kind='hist', bins=100,title='Log Loan Amt - Fraud', color='r',xlim=(-3, 10),ax= ax1) \n",
    "data_train.loc[data_train['isDefault'] == 0]['loanAmnt'].apply(np.log).plot(kind='hist', bins=100,title='Log Loan Amt - Not Fraud', color='b',xlim=(-3, 10),ax=ax2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 864x360 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "total = len(data_train)\n",
    "total_amt = data_train.groupby(['isDefault'])['loanAmnt'].sum().sum() \n",
    "plt.figure(figsize=(12,5)) \n",
    "plt.subplot(121)##1代表行，2代表列，所以一共有2个图，1代表此时绘制第一个图。\n",
    "plot_tr = sns.countplot(x='isDefault',data=data_train)#data_train‘isDefault’这个特征每种类别 的数量**\n",
    "plot_tr.set_title(\"Fraud Loan Distribution \\n 0: good user | 1: bad user\", fontsize=14) \n",
    "plot_tr.set_xlabel(\"Is fraud by count\", fontsize=16)\n",
    "plot_tr.set_ylabel('Count', fontsize=16)\n",
    "for p in plot_tr.patches:\n",
    "    height = p.get_height()\n",
    "    plot_tr.text(p.get_x()+p.get_width()/2.,\n",
    "    height + 3, '{:1.2f}%'.format(height/total*100), ha=\"center\", fontsize=15)\n",
    "\n",
    "percent_amt = (data_train.groupby(['isDefault'])['loanAmnt'].sum())\n",
    "percent_amt = percent_amt.reset_index()\n",
    "plt.subplot(122)\n",
    "plot_tr_2 = sns.barplot(x='isDefault', y='loanAmnt', dodge=True, data=percent_amt) \n",
    "plot_tr_2.set_title(\"Total Amount in loanAmnt \\n 0: good user | 1: bad user\", fontsize=14) \n",
    "plot_tr_2.set_xlabel(\"Is fraud by percent\", fontsize=16)\n",
    "plot_tr_2.set_ylabel('Total Loan Amount Scalar', fontsize=16) \n",
    "for p in plot_tr_2.patches:\n",
    "    height = p.get_height()\n",
    "    plot_tr_2.text(p.get_x()+p.get_width()/2.,\n",
    "    height + 3, '{:1.2f}%'.format(height/total_amt * 100), ha=\"center\", fontsize=15)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "时间格式处理与查看"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [],
   "source": [
    "#转化成时间格式\n",
    "data_train['issueDate'] = pd.to_datetime(data_train['issueDate'],format='%Y-%m-%d') \n",
    "startdate = datetime.datetime.strptime('2007-06-01', '%Y-%m-%d') \n",
    "data_train['issueDateDT'] = data_train['issueDate'].apply(lambda x: x-startdate).dt.days"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [],
   "source": [
    "#转化成时间格式\n",
    "data_test_a['issueDate'] = pd.to_datetime(data_train['issueDate'],format='%Y-%m-%d') \n",
    "startdate = datetime.datetime.strptime('2007-06-01', '%Y-%m-%d') \n",
    "data_test_a['issueDateDT'] = data_test_a['issueDate'].apply(lambda x: x-startdate).dt.days"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Distribution of issueDateDT dates')"
      ]
     },
     "execution_count": 53,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.hist(data_train['issueDateDT'], label='train')\n",
    "plt.hist(data_test_a['issueDateDT'], label='test')\n",
    "plt.legend()\n",
    "plt.title('Distribution of issueDateDT dates')\n",
    "#train 和 test issueDateDT 日期有重叠 所以使用基于时间的分割进行验证是不明智的"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "透视图"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [],
   "source": [
    "#透视图 索引可以有多个，“columns(列)”是可选的，聚合函数aggfunc最后是被应用到了变量“values”中你所 列举的项目上。\n",
    "pivot = pd.pivot_table(data_train, index=['grade'], columns=['issueDateDT'], values= ['loanAmnt'], aggfunc=np.sum)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead tr th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe thead tr:last-of-type th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th colspan=\"21\" halign=\"left\">loanAmnt</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>issueDateDT</th>\n",
       "      <th>0</th>\n",
       "      <th>30</th>\n",
       "      <th>61</th>\n",
       "      <th>92</th>\n",
       "      <th>122</th>\n",
       "      <th>153</th>\n",
       "      <th>183</th>\n",
       "      <th>214</th>\n",
       "      <th>245</th>\n",
       "      <th>274</th>\n",
       "      <th>...</th>\n",
       "      <th>3926</th>\n",
       "      <th>3957</th>\n",
       "      <th>3987</th>\n",
       "      <th>4018</th>\n",
       "      <th>4048</th>\n",
       "      <th>4079</th>\n",
       "      <th>4110</th>\n",
       "      <th>4140</th>\n",
       "      <th>4171</th>\n",
       "      <th>4201</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>grade</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>A</th>\n",
       "      <td>NaN</td>\n",
       "      <td>53650.0</td>\n",
       "      <td>42000.0</td>\n",
       "      <td>19500.0</td>\n",
       "      <td>34425.0</td>\n",
       "      <td>63950.0</td>\n",
       "      <td>43500.0</td>\n",
       "      <td>168825.0</td>\n",
       "      <td>85600.0</td>\n",
       "      <td>101825.0</td>\n",
       "      <td>...</td>\n",
       "      <td>13093850.0</td>\n",
       "      <td>11757325.0</td>\n",
       "      <td>11945975.0</td>\n",
       "      <td>9144000.0</td>\n",
       "      <td>7977650.0</td>\n",
       "      <td>6888900.0</td>\n",
       "      <td>5109800.0</td>\n",
       "      <td>3919275.0</td>\n",
       "      <td>2694025.0</td>\n",
       "      <td>2245625.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>B</th>\n",
       "      <td>NaN</td>\n",
       "      <td>13000.0</td>\n",
       "      <td>24000.0</td>\n",
       "      <td>32125.0</td>\n",
       "      <td>7025.0</td>\n",
       "      <td>95750.0</td>\n",
       "      <td>164300.0</td>\n",
       "      <td>303175.0</td>\n",
       "      <td>434425.0</td>\n",
       "      <td>538450.0</td>\n",
       "      <td>...</td>\n",
       "      <td>16863100.0</td>\n",
       "      <td>17275175.0</td>\n",
       "      <td>16217500.0</td>\n",
       "      <td>11431350.0</td>\n",
       "      <td>8967750.0</td>\n",
       "      <td>7572725.0</td>\n",
       "      <td>4884600.0</td>\n",
       "      <td>4329400.0</td>\n",
       "      <td>3922575.0</td>\n",
       "      <td>3257100.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>C</th>\n",
       "      <td>NaN</td>\n",
       "      <td>68750.0</td>\n",
       "      <td>8175.0</td>\n",
       "      <td>10000.0</td>\n",
       "      <td>61800.0</td>\n",
       "      <td>52550.0</td>\n",
       "      <td>175375.0</td>\n",
       "      <td>151100.0</td>\n",
       "      <td>243725.0</td>\n",
       "      <td>393150.0</td>\n",
       "      <td>...</td>\n",
       "      <td>17502375.0</td>\n",
       "      <td>17471500.0</td>\n",
       "      <td>16111225.0</td>\n",
       "      <td>11973675.0</td>\n",
       "      <td>10184450.0</td>\n",
       "      <td>7765000.0</td>\n",
       "      <td>5354450.0</td>\n",
       "      <td>4552600.0</td>\n",
       "      <td>2870050.0</td>\n",
       "      <td>2246250.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>D</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5500.0</td>\n",
       "      <td>2850.0</td>\n",
       "      <td>28625.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>167975.0</td>\n",
       "      <td>171325.0</td>\n",
       "      <td>192900.0</td>\n",
       "      <td>269325.0</td>\n",
       "      <td>...</td>\n",
       "      <td>11403075.0</td>\n",
       "      <td>10964150.0</td>\n",
       "      <td>10747675.0</td>\n",
       "      <td>7082050.0</td>\n",
       "      <td>7189625.0</td>\n",
       "      <td>5195700.0</td>\n",
       "      <td>3455175.0</td>\n",
       "      <td>3038500.0</td>\n",
       "      <td>2452375.0</td>\n",
       "      <td>1771750.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>E</th>\n",
       "      <td>7500.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>10000.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>17975.0</td>\n",
       "      <td>1500.0</td>\n",
       "      <td>94375.0</td>\n",
       "      <td>116450.0</td>\n",
       "      <td>42000.0</td>\n",
       "      <td>139775.0</td>\n",
       "      <td>...</td>\n",
       "      <td>3983050.0</td>\n",
       "      <td>3410125.0</td>\n",
       "      <td>3107150.0</td>\n",
       "      <td>2341825.0</td>\n",
       "      <td>2225675.0</td>\n",
       "      <td>1643675.0</td>\n",
       "      <td>1091025.0</td>\n",
       "      <td>1131625.0</td>\n",
       "      <td>883950.0</td>\n",
       "      <td>802425.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>F</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>31250.0</td>\n",
       "      <td>2125.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>49000.0</td>\n",
       "      <td>27000.0</td>\n",
       "      <td>43000.0</td>\n",
       "      <td>...</td>\n",
       "      <td>1074175.0</td>\n",
       "      <td>868925.0</td>\n",
       "      <td>761675.0</td>\n",
       "      <td>685325.0</td>\n",
       "      <td>665750.0</td>\n",
       "      <td>685200.0</td>\n",
       "      <td>316700.0</td>\n",
       "      <td>315075.0</td>\n",
       "      <td>72300.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>G</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>24625.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>56100.0</td>\n",
       "      <td>243275.0</td>\n",
       "      <td>224825.0</td>\n",
       "      <td>64050.0</td>\n",
       "      <td>198575.0</td>\n",
       "      <td>245825.0</td>\n",
       "      <td>53125.0</td>\n",
       "      <td>23750.0</td>\n",
       "      <td>25100.0</td>\n",
       "      <td>1000.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>7 rows × 139 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            loanAmnt                                                         \\\n",
       "issueDateDT     0        30       61       92       122      153       183    \n",
       "grade                                                                         \n",
       "A                NaN  53650.0  42000.0  19500.0  34425.0  63950.0   43500.0   \n",
       "B                NaN  13000.0  24000.0  32125.0   7025.0  95750.0  164300.0   \n",
       "C                NaN  68750.0   8175.0  10000.0  61800.0  52550.0  175375.0   \n",
       "D                NaN      NaN   5500.0   2850.0  28625.0      NaN  167975.0   \n",
       "E             7500.0      NaN  10000.0      NaN  17975.0   1500.0   94375.0   \n",
       "F                NaN      NaN  31250.0   2125.0      NaN      NaN       NaN   \n",
       "G                NaN      NaN      NaN      NaN      NaN      NaN       NaN   \n",
       "\n",
       "                                             ...                              \\\n",
       "issueDateDT      214       245       274     ...            3926        3957   \n",
       "grade                                        ...                               \n",
       "A            168825.0   85600.0  101825.0    ...      13093850.0  11757325.0   \n",
       "B            303175.0  434425.0  538450.0    ...      16863100.0  17275175.0   \n",
       "C            151100.0  243725.0  393150.0    ...      17502375.0  17471500.0   \n",
       "D            171325.0  192900.0  269325.0    ...      11403075.0  10964150.0   \n",
       "E            116450.0   42000.0  139775.0    ...       3983050.0   3410125.0   \n",
       "F             49000.0   27000.0   43000.0    ...       1074175.0    868925.0   \n",
       "G             24625.0       NaN       NaN    ...         56100.0    243275.0   \n",
       "\n",
       "                                                                       \\\n",
       "issueDateDT        3987        4018        4048       4079       4110   \n",
       "grade                                                                   \n",
       "A            11945975.0   9144000.0   7977650.0  6888900.0  5109800.0   \n",
       "B            16217500.0  11431350.0   8967750.0  7572725.0  4884600.0   \n",
       "C            16111225.0  11973675.0  10184450.0  7765000.0  5354450.0   \n",
       "D            10747675.0   7082050.0   7189625.0  5195700.0  3455175.0   \n",
       "E             3107150.0   2341825.0   2225675.0  1643675.0  1091025.0   \n",
       "F              761675.0    685325.0    665750.0   685200.0   316700.0   \n",
       "G              224825.0     64050.0    198575.0   245825.0    53125.0   \n",
       "\n",
       "                                              \n",
       "issueDateDT       4140       4171       4201  \n",
       "grade                                         \n",
       "A            3919275.0  2694025.0  2245625.0  \n",
       "B            4329400.0  3922575.0  3257100.0  \n",
       "C            4552600.0  2870050.0  2246250.0  \n",
       "D            3038500.0  2452375.0  1771750.0  \n",
       "E            1131625.0   883950.0   802425.0  \n",
       "F             315075.0    72300.0        NaN  \n",
       "G              23750.0    25100.0     1000.0  \n",
       "\n",
       "[7 rows x 139 columns]"
      ]
     },
     "execution_count": 55,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pivot"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 总结\n",
    "数据探索性分析是我们初步了解数据，熟悉数据为特征工程做准备的阶段，甚至很多时候EDA阶段提取出来的特 征可以直接当作规则来用。可见EDA的重要性，这个阶段的主要工作还是借助于各个简单的统计量来对数据整体 的了解，分析各个类型变量相互之间的关系，以及用合适的图形可视化出来直观观察。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}
